COG-MHEAR: Towards cognitively-inspired 5G-IoT enabled, multi-modal Hearing Aids
Lead Research Organisation:
Edinburgh Napier University
Department Name: School of Computing
Abstract
Currently, only 40% of people who could benefit from Hearing Aids (HAs) have them, and most people who have HA devices don't use them often enough. There is social stigma around using visible HAs ('fear of looking old'), they require a lot of conscious effort to concentrate on different sounds and speakers, and only limited use is made of speech enhancement - making the spoken words (which are often the most important aspect of hearing to people) easier to distinguish. It is not enough just to make everything louder!
To transform hearing care by 2050, we aim to completely re-think the way HAs are designed. Our transformative approach - for the first time - draws on the cognitive principles of normal hearing. Listeners naturally combine information from both their ears and eyes: we use our eyes to help us hear. We will create "multi-modal" aids which not only amplify sounds but contextually use simultaneously collected information from a range of sensors to improve speech intelligibility. For example, a large amount of information about the words said by a person is conveyed in visual information, in the movements of the speaker's lips, hand gestures, and similar. This is ignored by current commercial HAs and could be fed into the speech enhancement process. We can also use wearable sensors (embedded within the HA itself) to estimate listening effort and its impact on the person, and use this to tell whether the speech enhancement process is actually helping or not.
Creating these multi-modal "audio-visual" HAs raises many formidable technical challenges which need to be tackled holistically. Making use of lip movements traditionally requires a video camera filming the speaker, which introduces privacy questions. We can overcome some of these questions by encrypting the data as soon as it is collected, and we will pioneer new approaches for processing and understanding the video data while it stays encrypted. We aim to never access the raw video data, but still to use it as a useful source of information. To complement this, we will also investigate methods for remote lip reading without using a video feed, instead exploring the use of radio signals for remote monitoring.
Adding in these new sensors and the processing that is required to make sense of the data produced will place a significant additional power and miniaturization burden on the HA device. We will need to make our sophisticated visual and sound processing algorithms operate with minimum power and minimum delay, and will achieve this by making dedicated hardware implementations, accelerating the key processing steps. In the long term, we aim for all processing to be done in the HA itself - keeping data local to the person for privacy. In the shorter term, some processing will need to be done in the cloud (as it is too power intensive) and we will create new very low latency (<10ms) interfaces to cloud infrastructure to avoid delays between when a word is "seen" being spoken and when it is heard. We also plan to utilize advances in flexible electronics (e-skin) and antenna design to make the overall unit as small, discreet and usable as possible.
Participatory design and co-production with HA manufacturers, clinicians and end-users will be central to all of the above, guiding all of the decisions made in terms of design, prioritisation and form factor. Our strong User Group, which includes Sonova, Nokia/Bell Labs, Deaf Scotland and Action on Hearing Loss will serve to maximise the impact of our ambitious research programme. The outcomes of our work will be fully integrated, software and hardware prototypes, that will be clinically evaluated using listening and intelligibility tests with hearing-impaired volunteers in a range of modern noisy reverberant environments. The success of our ambitious vision will be measured in terms of how the fundamental advancements posited by our demonstrator programme will reshape the HA landscape over the next decade.
To transform hearing care by 2050, we aim to completely re-think the way HAs are designed. Our transformative approach - for the first time - draws on the cognitive principles of normal hearing. Listeners naturally combine information from both their ears and eyes: we use our eyes to help us hear. We will create "multi-modal" aids which not only amplify sounds but contextually use simultaneously collected information from a range of sensors to improve speech intelligibility. For example, a large amount of information about the words said by a person is conveyed in visual information, in the movements of the speaker's lips, hand gestures, and similar. This is ignored by current commercial HAs and could be fed into the speech enhancement process. We can also use wearable sensors (embedded within the HA itself) to estimate listening effort and its impact on the person, and use this to tell whether the speech enhancement process is actually helping or not.
Creating these multi-modal "audio-visual" HAs raises many formidable technical challenges which need to be tackled holistically. Making use of lip movements traditionally requires a video camera filming the speaker, which introduces privacy questions. We can overcome some of these questions by encrypting the data as soon as it is collected, and we will pioneer new approaches for processing and understanding the video data while it stays encrypted. We aim to never access the raw video data, but still to use it as a useful source of information. To complement this, we will also investigate methods for remote lip reading without using a video feed, instead exploring the use of radio signals for remote monitoring.
Adding in these new sensors and the processing that is required to make sense of the data produced will place a significant additional power and miniaturization burden on the HA device. We will need to make our sophisticated visual and sound processing algorithms operate with minimum power and minimum delay, and will achieve this by making dedicated hardware implementations, accelerating the key processing steps. In the long term, we aim for all processing to be done in the HA itself - keeping data local to the person for privacy. In the shorter term, some processing will need to be done in the cloud (as it is too power intensive) and we will create new very low latency (<10ms) interfaces to cloud infrastructure to avoid delays between when a word is "seen" being spoken and when it is heard. We also plan to utilize advances in flexible electronics (e-skin) and antenna design to make the overall unit as small, discreet and usable as possible.
Participatory design and co-production with HA manufacturers, clinicians and end-users will be central to all of the above, guiding all of the decisions made in terms of design, prioritisation and form factor. Our strong User Group, which includes Sonova, Nokia/Bell Labs, Deaf Scotland and Action on Hearing Loss will serve to maximise the impact of our ambitious research programme. The outcomes of our work will be fully integrated, software and hardware prototypes, that will be clinically evaluated using listening and intelligibility tests with hearing-impaired volunteers in a range of modern noisy reverberant environments. The success of our ambitious vision will be measured in terms of how the fundamental advancements posited by our demonstrator programme will reshape the HA landscape over the next decade.
Planned Impact
Significant impact beyond the academic environment is envisaged through this multi-disciplinary programme:
*Impact on people with hearing loss*
Over 10 million people in the UK (~350 million worldwide) currently suffer from debilitating hearing loss, at a cost of ~£450M/year to the NHS, and this figure is expected to rise to 14.5 million by 2031. People with serious hearing loss often find themselves socially isolated with a range of adverse health consequences. Even a modest improvement in hearing however, can have a significant impact on an individual's social and work life. Our proposed technologies will transform real-time, privacy-preserving and domain-independent learning capabilities, to deliver robust speech intelligibility enhancement and end-user cognitive load management, in the hearing aids (HAs) of 2050. Our technical work programme is focused on this contribution, and the wide number of released societal and individual benefits that follow from it. For example, the data we can obtain from our pilot (on/off-chip) HA fitting and clinical validation, in smart assistive care homes and other real-life environments, could potentially enable: remote fitting, and usage training of HAs for end-users and audiologists - resulting in resource savings and relevance in developing countries. In care homes, where hearing loss affects ~90%, a well-functioning communication channel (even by remote communication) in which the emotional state can be securely sensed and transported, would be an ambitious clinically relevant use case. This would also benefit the visually impaired as it complements the visual processing in speech perception.
*Hearing aid industry*
Our proposed audio-visual (AV) HAs can have a considerable impact on the HA industry, as demand for future AV aids should rapidly complement inferior Audio-only devices. The UK's global reputation in hearing research could thus be transformed simulating major global HA manufacturing. There are clear precedents for hearing science rapidly transforming hearing technology, e.g. multiple microphone processing and frequency compression have been commercialised to great effect. COG-MHEAR foresees AV processing as the next timely step forward, as previous barriers to AV processing are being overcome: wireless 5G and Internet of Things (IoT) technologies can free computation from having to be performed on the device itself, and wearable computing devices are becoming powerful enough to perform real-time face tracking and feature extraction. AV HAs will also impact on industry standards for HA evaluation and clinical standards for hearing loss assessment. Plans for realising industrial impacts are detailed in the Pathways to Impact and Workplan.
*Applications beyond hearing aids*
We foresee impact in several areas (see Impact Pathways), including cochlear implant signal processing, automatic speech recognition systems, multisensory integration, general auditory systems engineering, and clinical, computational, cognitive and auditory neuroscience. Beyond HAs, novel multimodal ecological momentary assessment tools could be developed, transforming existing sparse, unimodal commercial systems of our User Group members, e.g. Sonova. These could be exploited to personalise the design and usability of other medical instruments to enhance personal product experience. Our proposed wireless-based emotion detection system could extend to emotion-sensitive robotic assistants/companions, that could be of interest to smart care homes. Beyond health, our research will deliver a step change in the critical mass of UK engineering and physical science skills to tackle emerging challenges in signal processing. The potential of our disruptive technology can be exploited in teleconferencing and extremely noisy environments e.g. dynamic environments and situations where ear defenders are worn, such as emergency and disaster response and battlefield environments.
*Impact on people with hearing loss*
Over 10 million people in the UK (~350 million worldwide) currently suffer from debilitating hearing loss, at a cost of ~£450M/year to the NHS, and this figure is expected to rise to 14.5 million by 2031. People with serious hearing loss often find themselves socially isolated with a range of adverse health consequences. Even a modest improvement in hearing however, can have a significant impact on an individual's social and work life. Our proposed technologies will transform real-time, privacy-preserving and domain-independent learning capabilities, to deliver robust speech intelligibility enhancement and end-user cognitive load management, in the hearing aids (HAs) of 2050. Our technical work programme is focused on this contribution, and the wide number of released societal and individual benefits that follow from it. For example, the data we can obtain from our pilot (on/off-chip) HA fitting and clinical validation, in smart assistive care homes and other real-life environments, could potentially enable: remote fitting, and usage training of HAs for end-users and audiologists - resulting in resource savings and relevance in developing countries. In care homes, where hearing loss affects ~90%, a well-functioning communication channel (even by remote communication) in which the emotional state can be securely sensed and transported, would be an ambitious clinically relevant use case. This would also benefit the visually impaired as it complements the visual processing in speech perception.
*Hearing aid industry*
Our proposed audio-visual (AV) HAs can have a considerable impact on the HA industry, as demand for future AV aids should rapidly complement inferior Audio-only devices. The UK's global reputation in hearing research could thus be transformed simulating major global HA manufacturing. There are clear precedents for hearing science rapidly transforming hearing technology, e.g. multiple microphone processing and frequency compression have been commercialised to great effect. COG-MHEAR foresees AV processing as the next timely step forward, as previous barriers to AV processing are being overcome: wireless 5G and Internet of Things (IoT) technologies can free computation from having to be performed on the device itself, and wearable computing devices are becoming powerful enough to perform real-time face tracking and feature extraction. AV HAs will also impact on industry standards for HA evaluation and clinical standards for hearing loss assessment. Plans for realising industrial impacts are detailed in the Pathways to Impact and Workplan.
*Applications beyond hearing aids*
We foresee impact in several areas (see Impact Pathways), including cochlear implant signal processing, automatic speech recognition systems, multisensory integration, general auditory systems engineering, and clinical, computational, cognitive and auditory neuroscience. Beyond HAs, novel multimodal ecological momentary assessment tools could be developed, transforming existing sparse, unimodal commercial systems of our User Group members, e.g. Sonova. These could be exploited to personalise the design and usability of other medical instruments to enhance personal product experience. Our proposed wireless-based emotion detection system could extend to emotion-sensitive robotic assistants/companions, that could be of interest to smart care homes. Beyond health, our research will deliver a step change in the critical mass of UK engineering and physical science skills to tackle emerging challenges in signal processing. The potential of our disruptive technology can be exploited in teleconferencing and extremely noisy environments e.g. dynamic environments and situations where ear defenders are worn, such as emergency and disaster response and battlefield environments.
Organisations
- Edinburgh Napier University (Lead Research Organisation)
- Sao Paulo State University (Collaboration)
- University of Portsmouth (Collaboration)
- Glasgow Royal Infirmary (Collaboration)
- University of Surrey (Collaboration)
- Duke Kunshan University (Collaboration)
- University of Reggio Calabria (Collaboration)
- University of Glasgow (Collaboration)
- University of Science and Technology of China USTC (Collaboration)
- Heriot-Watt University (Collaboration)
- University of Essex (Collaboration)
- InterDigital (Collaboration)
- University of Southampton (Collaboration)
- University of Nottingham (Collaboration)
- Academia Sinica (Collaboration)
- Sapienza University of Rome (Collaboration)
- University of Leicester (Collaboration)
- Action on Hearing Loss (Collaboration)
- Trinity College Dublin (Collaboration)
- Carl von Ossietzky University of Oldenburg (Collaboration)
- IEEE Industry Applications Society (Collaboration)
- Anhui University (Collaboration)
- UNIVERSITY OF EDINBURGH (Collaboration)
- Sonova (Collaboration)
- EARSWITCH LTD (Collaboration)
- RNID (Royal Natnl Inst for Deaf People) (Project Partner)
- NHS Lothian (Project Partner)
- The Data Lab (Project Partner)
- deafscotland (Project Partner)
- University of Manchester (Project Partner)
- Sonova AG (Project Partner)
- Nokia (Project Partner)
- Digital Health and Care Institute (Project Partner)
- UNIVERSITY COLLEGE LONDON (Project Partner)
- Alpha Data Parallel Systems Ltd (UK) (Project Partner)
Publications
Ashleibta A
(2021)
Non-Invasive RF Sensing for Detecting Breathing Abnormalities Using Software Defined Radios
in IEEE Sensors Journal
Zou Z
(2022)
A novel multimodal fusion network based on a joint-coding model for lane line segmentation
in Information Fusion
Zhang L
(2022)
DNet-CNet: a novel cascaded deep network for real-time lane detection and classification
in Journal of Ambient Intelligence and Humanized Computing
Li H
(2022)
Attributes Guided Feature Learning for Vehicle Re-Identification
in IEEE Transactions on Emerging Topics in Computational Intelligence
Gao F
(2022)
Ellipse Encoding for Arbitrary-Oriented SAR Ship Detection Based on Dynamic Key Points
in IEEE Transactions on Geoscience and Remote Sensing
Passos L
(2022)
Multimodal Audio-Visual Information Fusion Using Canonical-Correlated Graph Neural Network for Energy-Efficient Speech Enhancement
in SSRN Electronic Journal
Abbes W
(2022)
An Enhanced Binary Particle Swarm Optimization (E-BPSO) algorithm for service placement in hybrid cloud platforms
in Neural Computing and Applications
Khan S
(2022)
Evaluation of Unobtrusive Microwave Sensors in Healthcare 4.0-Toward the Creation of Digital-Twin Model.
in Sensors (Basel, Switzerland)
Mu Y
(2022)
Federated Learning in Massive MIMO 6G Networks: Convergence Analysis and Communication-Efficient Design
in IEEE Transactions on Network Science and Engineering
Khan S
(2022)
Digital Twin Perspective of Fourth Industrial and Healthcare Revolution
in IEEE Access
Ge H
(2022)
Generalized superimposed training for RIS-aided cell-free massive MIMO-OFDM networks
in Journal of Communications and Networks
Biaggi L
(2022)
FEMa-FS: Finite Element Machines for Feature Selection
Ali SM
(2022)
Design of Flexible Meander Line Antenna for Healthcare in Wireless Body Area Network Systems.
in Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Cambria E
(2022)
Guest Editorial: A Decade of Sentic Computing.
in Cognitive computation
Usman M
(2022)
Intelligent wireless walls for contactless in-home monitoring.
in Light, science & applications
Zhang J
(2022)
In-Band-Full-Duplex Integrated Sensing and Communications for IAB Networks
in IEEE Transactions on Vehicular Technology
Ali SM
(2022)
Low-profile Button Sensor Antenna Design for Wireless Medical Body Area Networks.
in Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
| Description | Key findings and achievements of the COG-MHEAR Award to date include: (1) Participatory co-design with end users and ongoing evaluation of the world's first real-time multimodal hearing assistive technology demonstrators, including hardware and software implementations, that autonomously adapt to the nature and quality of their visual and acoustic environmental inputs. This has led to significantly enhanced intelligibility in noise, with reduced listening effort or cognitive load. A software prototype of the MVP has also been optimised for use in web-based video communication, which has been shown to transform the listening and conversational experience for both normal and hearing-impaired individuals. (2) The developed software and hardware prototypes have been evaluated through integration with commercial hearing aids. In pilot clinical testing with hearing aid users, our prototypes have shown the potential to transform the performance of current state-of-the-art commercial aids, delivering a statistically significant improvement in listening and intelligibility experiences in real-world, noisy environments. Prototype demonstrations have been regularly showcased both nationally and globally, including by organising international workshops and challenges as part of leading international conferences, such as the premier 2022 IEEE EMBC, the 2023 IEEE ICASSP, ISCA's flagship 2023 Interspeech and 2024 Interspeech conferences, the biennial 2024 IHCON, the 2024 WCA, and in supplements to the journal JASA. Patent applications have been submitted for developed prototype technologies, and funding applications are in progress for spinout formation. (3) Development of the world's first web-based multi-modal speech enhancement demonstrator tool, which has been made openly available as a benchmark resource for research and innovation. This tool shows how recordings of speech in noisy environments can be multi-modally processed, both locally and in the cloud, to remove background noise and make the speech easier to hear. (4) The disruptive development of a robust privacy-preserving radio frequency (RF)-based lip-reading framework to address user privacy concerns associated with the use of conventional (e.g., video camera-based) sensing approaches in future multi-modal hearing aids. The innovative framework has demonstrated a unique ability to read lips under face masks by employing Wi-Fi and radar as enablers of RF sensing technology. The pioneering study has been published in Nature Communications, and datasets have been made openly available. (5) In a user group-prioritised use case, a novel privacy-preserving radio-frequency-based approach has been developed for British Sign Language (BSL) detection, to aid communication for hearing-aid users who use sign language. (6) COG-MHEAR has pioneered user and environmentally context-aware solutions for multimodal hearing-aid users, leveraging off-the-shelf Wi-Fi networks for contextual activity monitoring and indoor localisation via intelligent wireless walls. Key findings were published in Nature Light, and associated datasets have been made openly available as new benchmarks for the global research community. (7) Organisation of the world's first large-scale audio-visual speech enhancement (AVSEC) Challenge, utilising real-world TED Talks. The Challenge was organised as part of the leading IEEE Spoken Language Technology (SLT) Workshop, Qatar, 9-12 Jan 2023. Our team developed a new baseline pre-trained deep neural network model, which was made openly available to participants, along with raw and pre-processed audio-visual datasets-derived from real-world TED talk videos-for training and development of new audio-visual models to perform speech enhancement and speaker separation at signal-to-noise ratio (SNR) levels that were significantly more challenging than typically used in audio-only scenarios. The Challenge evaluation utilised established objective measures (such as STOI and PESQ, for which scripts were provided to participants), as well as a new audio-visual intelligibility evaluation method developed by the COG-MHEAR teams for subjective evaluation with human subjects. The new baseline model, real-world datasets, and subjective audio-visual intelligibility testing method are continuing to be exploited by researchers in speech and natural language communication and hearing assistive technology applications. Our COG-MHEAR team, based at Edinburgh Napier University, won first place in the Challenge, based on an independent subjective audio-visual evaluation carried out by researchers at the University of Edinburgh. This demonstrated the efficacy of our novel audio-visual speech enhancement models compared to global benchmark models. (8) Organisation of the 2nd COG-MHEAR International Audio-Visual Speech Enhancement Challenge (AVSEC-2), which featured as an approved Challenge at IEEE ASRU 2023, 16-20 Dec 2023. AVSEC-2 received a higher number of submissions compared to the first challenge, and we were pleased to see high-profile companies, such as Mitsubishi, among the participants. Moreover, there was an increase in the performance of the best-performing systems. (9) Organisation of the 3rd COG-MHEAR International Audio-Visual Speech Enhancement Challenge (AVSEC-3), which featured as a Satellite Workshop at 2024 Interspeech. AVSEC-3 featured a first-of-its-kind low-latency AVSEC track and continued to see an increase in the performance of the best-performing systems. The data produced from the challenges has enabled us to gain further understanding about the role that features of the audio and visual components play in intelligibility; we also investigated how intelligibility is affected when audio-only and audio-visual stimuli are presented, leading to important findings about the efficacy of speech enhancement in in-person settings. The annual challenges have provided excellent global advocacy for COG-MHEAR, bringing opportunities to strengthen the audio-visual speech enhancement community and bringing together interdisciplinary researchers to work towards improving future speech and hearing technologies. Challenge prizes for winners and runners-up are sponsored by Sonova. (10) Our ongoing workshops with hearing aid (HA) users included an in-depth workshop organised in November 2023. The pilot testing in a range of realistic, challenging noisy environments found that our current WP1 technology assisted with clarity of speech in noise across all participants with hearing loss. However, user feedback also guided us to make several improvements to the tests. These included: minimising unnecessary noise that quickly causes fatigue; simplifying questions; ensuring that tests are 'double blind' for both the talker whose voice is to be identified and the participant; and making participants aware that some of the tests are by design very difficult. In a further session with HA users, industry representatives, and audiologists, we asked audiologists what they think of our proposed AV test design, with a particular focus on the instructions to be given: would they be explicit enough for patients to perform the tests without clinical assistance? Attendees at the meeting advised on ways of clarifying and simplifying the tests. (11) Organisation of the 2022 UK Speech Conference in Edinburgh, with 180+ participants. This showcased COG-MHEAR's world-leading research to the wider UK speech technology community and led to ongoing development of new collaborations and networks, including a new UK Special Interest Group on Speech-based Multi-Modal Processing (co-led by the COG-MHEAR PI). (12) Organisation of a Special Session on "Multi-modal hearing and hearing-assistive technologies" at the 2023 Basic Auditory Science (BAS) Conference, Imperial College London, 21-22 September 2023. This included 14 accepted presentations, including by COG-MHEAR researchers. (13) Organisation of the first international 2023 IEEE ICASSP Satellite Workshop on "Advances in Multi-modal Hearing Assistive Technologies (AMHAT)," 10 June 2023. This featured 10 accepted presentations, a panel discussion on challenges and opportunities in designing and evaluating future multi-modal hearing aids, and invited keynotes by academic and industry experts, including Prof Tsao (Taiwan) and Dr Derleth (Sonova). (14) Organisation of the 2023 INTERSPEECH Special Session on "Multi-talker methods in speech processing", 20-24 Aug 2023. This featured 16 presentations from industry and academic researchers. (15) Organisation of the 2024 INTERSPEECH Satellite Workshop on "3rd COG-MHEAR International Audio-Visual Speech Enhancement Challenge (AVSEC-3)", 1 Sep 2024. This featured 24 presentations from academic and industry researchers, published in peer-reviewed workshop proceedings. Authors of selected AVSEC-3 Workshop papers (including winners and runners-up of each Challenge Track) were invited to submit significantly extended papers for consideration in a Special Issue (guest edited by the COG-MHEAR PI and our world-leading collaborators) for the impactful IEEE Journal of Selected Topics in Signal Processing (JSTSP) on "Deep Multimodal Speech Enhancement and Separation." (16) Showcasing and user evaluation of our prototype demonstrators at COG-MHEAR User Group and Industry Workshops and international events, including the 2023 and 2024 INTERSPEECH Show and Tell, 2023 and 2024 IEEE ISCAS, 2023 ICASSP, Acoustics 2023, IHCON 2024, and the World Congress of Audiology 2024. (17) Global dissemination and engagement, including invited articles in ENT and Audiology News (a bi-monthly print publication and online forum distributed to over 140 countries), and participation in public events such as the Edinburgh Fringe Festival 2023. Ongoing public engagement activities include media coverage and invited talks at events like TEDWomen, Cabaret of Dangerous Ideas (Hearing Aids Don't Work!) at the Edinburgh Fringe Festival 2023, and the Soapbox Science Event 2024. (18) Continuing engagement with policymakers and advocacy for COG-MHEAR research. Examples include contributions by Casson to standards for Brain-Computer Interfaces, the Innovate UK roadmap for the electronics industry, and the RAE green paper on pillar 8 of the Industrial Strategy (Cultivating World Leading Sectors). Bell participated in a workshop on AI regulation for the public sector and meetings with OFCOM to explore collaborations on online safety. Hussain participated in the UKRI EPSRC Healthcare Strategy Workshop Series and contributed to interdisciplinary research assessment strategies as Chair Panel member of the UKRI Interdisciplinary Assessment College. He is also coordinating national consultations as an elected Executive Committee member of the UK Computing Research Committee (UKCRC), the expert panel of BCS, The Chartered Institute for IT, and the Council of Professors and Heads of Computing (CPHC) for UK computing research. Sellathurai and Imran contributed to DCMS's 5G RuralFirst to enable future e-health services for rural communities. Hart was part of a government Steering Group to oversee the development of the Scottish Government AI Strategy. Sellathurai contributed to the new IEEE Standard on P2933 and the IEEE Standard Association Age Tek Webinar series on Clinical Supports for the Aging. |
| Exploitation Route | Key outcomes of this funding are being taken forward and put to use by others in several impactful ways, including: (1) Industry and Commercial Hearing Assistive Technology Applications: The transformative real-time multimodal hearing assistive technology demonstrators developed in this programme, including software and hardware implementations, have been integrated into commercial hearing aids and communications systems, transforming their performance in a range of challenging real noisy environments. By leveraging the developed AI-powered personalised prototypes, hearing aid manufacturers can significantly improve the intelligibility and listening experience and reduce listening effort (cognitive load) of hearing aid users. We are continuing to work with partner commercial hearing aid companies interested in exploiting our innovations to create more adaptive, context-aware devices that offer significantly improved real-world performance. (2) Open-Source Resources: Our first-of-its-kind web-based multi-modal speech enhancement tool, realistic datasets, and pre-trained models developed in this programme, including through organisation of annual industry-sponsored AVSEC challenges and workshops, have been made openly available. These resources continue to allow other researchers and developers to use them to advance their own work in assistive hearing and speech communication technologies. The benchmark resources provide an accessible platform for exploring new methods, improving current systems, and conducting further research in this interdisciplinary space. (3) Privacy-Preserving Technologies: Pioneering work on novel privacy-preserving radio-frequency-based lip-reading and sign language detection systems is being evaluated for adoption in future hearing aids and assistive technologies, addressing privacy concerns while enhancing the user experience. By adopting RF-based systems, hearing aids can detect speech and lip movements without relying on video cameras, thus protecting user privacy. (4) Collaboration and Innovation Networks: The global workshops, challenges, and international collaborations established as part of COG-MHEAR have created a strong community of world-leading researchers and industry professionals. The cross-disciplinary networks are continuing to drive innovation in multimodal hearing technologies to benefit people with hearing impairments worldwide. Our ongoing industry-sponsored international AVSEC challenges continue to provide researchers and innovators with a unique forum to showcase their work and develop new solutions that can have a broad impact across multimodal hearing and speech technologies and applications. (5) Policy Influence and Industry Standards: COG-MHEAR's ongoing engagement with policymakers, including coordination of national consultations and contributions to industry standards (e.g., IEEE standards, UKRI EPSRC Healthcare Strategy), ensures that the findings of this cross-disciplinary programme are directly translated into the development of regulations, frameworks, and strategies that will shape the future of hearing and speech technologies and their integration into broader healthcare and communication systems. Policymakers can use these outcomes to guide decisions on funding, regulation, and the ethical use of AI in a range of assistive and healthcare technologies. (6) Real-World Testing and User Feedback: The ongoing engagement with end-users, including those who are hearing impaired, allows for continuous testing, feedback, refinement and personalisation of the developed technologies. The user-driven insights will help guide future developments and ensure that the disruptive technologies remain practical and beneficial for the target population. This ensures that the outcomes are relevant and can be put to use in real-world settings. In conclusion, the innovative outcomes of this funding continue to drive significant advancements in hearing-assistive technologies, promote interdisciplinary collaboration, influence policy, and enhance the daily lives of individuals with hearing impairments worldwide. |
| Sectors | Aerospace Defence and Marine Communities and Social Services/Policy Digital/Communication/Information Technologies (including Software) Electronics Environment Healthcare Leisure Activities including Sports Recreation and Tourism Security and Diplomacy Transport Other |
| URL | https://cogmhear.org/ |
| Description | COG-MHEAR's overall impact strategy aims to shorten the time to translation for our pioneering research work, ensuring that the fundamental research performed is ultimately relevant to hearing health care and practice. Within this, we aim for broad impacts in engineering, AI, health, and social care. Our research to date has included work applicable to healthcare areas of economic and social importance, including computer vision, speech and natural language dialogue systems, embedded robots, neuroscience, flexible electronics, and wireless systems engineering. This has led to significant additional funding awarded to COG-MHEAR investigators, broadening COG-MHEAR's national and global impact in a number of key research and innovation areas. For example, a new Defense and Security Accelerator funding award by the Defence Science and Technology Laboratory has led to the development of ULTRA-Earswitch: innovative tactical in-ear ultrasound-driven headphones enabling communication, noise protection, and hands-free control without reducing situational awareness. The COG-MHEAR award has led to 3 patents, with commercial exploitation being explored through ongoing licensing discussions and spinout formation. Key findings are being taken forward and put to use by others in several impactful ways, including: (1) Industry and Commercial Hearing Assistive Technology Applications: The transformative real-time multimodal hearing assistive technology demonstrators developed in this programme, including software and hardware implementations, have been integrated into commercial hearing aids and communications systems, transforming their performance in a range of challenging real noisy environments. By leveraging the developed AI-powered personalised prototypes, hearing aid manufacturers can significantly improve the intelligibility and listening experience and reduce listening effort (cognitive load) of hearing aid users. We are continuing to work with partner commercial hearing aid companies interested in exploiting our innovations to create more adaptive, context-aware devices that offer significantly improved real-world performance. (2) Open-Source Resources: Our first-of-its-kind web-based multi-modal speech enhancement tool, realistic datasets, and pre-trained models developed in this programme, including through organisation of annual industry-sponsored AVSEC challenges and workshops, have been made openly available. These resources continue to allow other researchers and developers to use them to advance their own work in assistive hearing and speech communication technologies. The benchmark resources provide an accessible platform for exploring new methods, improving current systems, and conducting further research in this interdisciplinary space. (3) Privacy-Preserving Technologies: Pioneering work on novel privacy-preserving radio-frequency-based lip-reading and sign language detection systems is being evaluated for adoption in future hearing aids and assistive technologies, addressing privacy concerns while enhancing the user experience. By adopting RF-based systems, hearing aids can detect speech and lip movements without relying on video cameras, thus protecting user privacy. (4) Collaboration and Innovation Networks: The global workshops, challenges, and international collaborations established as part of COG-MHEAR have created a strong community of world-leading researchers and industry professionals. The cross-disciplinary networks are continuing to drive innovation in multimodal hearing technologies to benefit people with hearing impairments worldwide. Our ongoing industry-sponsored international AVSEC challenges continue to provide researchers and innovators with a unique forum to showcase their work and develop new solutions that can have a broad impact across multimodal hearing and speech technologies and applications. (5) Policy Influence and Industry Standards: COG-MHEAR's ongoing engagement with policymakers, including coordination of national consultations and contributions to industry standards (e.g., IEEE standards, UKRI EPSRC Healthcare Strategy), ensures that the findings of this cross-disciplinary programme are directly translated into the development of regulations, frameworks, and strategies that will shape the future of hearing and speech technologies and their integration into broader healthcare and communication systems. Policymakers can use these outcomes to guide decisions on funding, regulation, and the ethical use of AI in a range of assistive and healthcare technologies. (6) Real-World Testing and User Feedback: The ongoing engagement with end-users, including those who are hearing impaired, allows for continuous testing, feedback, refinement and personalisation of the developed technologies. The user-driven insights will help guide future developments and ensure that the disruptive technologies remain practical and beneficial for the target population. This ensures that the outcomes are relevant and can be put to use in real-world settings. In conclusion, the innovative findings of this award continue to drive significant advancements in hearing-assistive technologies, promote interdisciplinary collaboration, influence policy, and enhance the daily lives of individuals with hearing impairments worldwide. |
| First Year Of Impact | 2022 |
| Sector | Aerospace, Defence and Marine,Communities and Social Services/Policy,Digital/Communication/Information Technologies (including Software),Education,Electronics,Energy,Environment,Healthcare,Leisure Activities, including Sports, Recreation and Tourism,Government, Democracy and Justice,Manufacturing, including Industrial Biotechology,Culture, Heritage, Museums and Collections,Pharmaceuticals and Medical Biotechnology,Retail,Security and Diplomacy,Transport |
| Impact Types | Cultural Societal Economic Policy & public services |
| Description | Scottish Science Advisory Board member |
| Geographic Reach | National |
| Policy Influence Type | Participation in a guidance/advisory committee |
| Description | Artificial Intelligence (AI) - powered dashboard for Covid-19 related public sentiment and opinion mining in social media platforms |
| Amount | £135,104 (GBP) |
| Funding ID | COV/NAP/20/07 |
| Organisation | Chief Scientist Office |
| Sector | Public |
| Country | United Kingdom |
| Start | 04/2020 |
| End | 10/2020 |
| Description | Closed-loop Neural Interface Technologies (Close-NIT) Network Plus |
| Amount | £1,106,216 (GBP) |
| Funding ID | EP/W035081/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 07/2022 |
| End | 07/2025 |
| Description | Cross-lingual Audio-visual Speech Enhancement based on Deep Multimodal Learning |
| Amount | £12,000 (GBP) |
| Organisation | Royal Society of Edinburgh (RSE) |
| Sector | Charity/Non Profit |
| Country | United Kingdom |
| Start | 05/2023 |
| End | 05/2025 |
| Description | Developing SysteMatic: Prevention, Precision and Equity by Design for People Living with Multiple Long-term Conditions |
| Amount | £204,995 (GBP) |
| Organisation | National Institute for Health and Care Research |
| Sector | Public |
| Country | United Kingdom |
| Start | 06/2023 |
| End | 12/2024 |
| Description | Empowering Practical Interfacing of Quantum Computing (EPIQC) |
| Amount | £2,448,091 (GBP) |
| Funding ID | EP/W032627/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 03/2022 |
| End | 04/2026 |
| Description | Evaluation of Federated Machine Unlearning using Membership Inference Attacks |
| Amount | £73,564 (GBP) |
| Organisation | Carnegie Trust |
| Sector | Charity/Non Profit |
| Country | United Kingdom |
| Start | 09/2023 |
| End | 09/2026 |
| Description | Facilitating health and wellbeing by developing systems for early recognition of urinary tract infections - Feather |
| Amount | £1,100,918 (GBP) |
| Funding ID | EP/W031493/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 11/2022 |
| End | 10/2025 |
| Description | Millimetre-wave and Terahertz On-chip Circuit Test Cluster for 6G Communications and Beyond (TIC6G) |
| Amount | £2,629,606 (GBP) |
| Funding ID | EP/W006448/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 01/2022 |
| End | 12/2023 |
| Description | Natural Language Generation for Low-resource Domains |
| Amount | £416,848 (GBP) |
| Funding ID | EP/T024917/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 03/2021 |
| End | 02/2024 |
| Description | Platform Driving The Ultimate Connectivity |
| Amount | £2,030,861 (GBP) |
| Funding ID | EP/X04047X/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 04/2023 |
| End | 04/2026 |
| Description | Protecting Minority Ethnic Communities Online (PRIME) |
| Amount | £1,466,412 (GBP) |
| Funding ID | EP/W032333/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 03/2022 |
| End | 03/2025 |
| Description | SNOW: Wearable Nano-Opto-electro-mechanic Systems |
| Amount | £246,178 (GBP) |
| Funding ID | EP/X034690/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 04/2023 |
| End | 10/2026 |
| Description | Sig Soli Scholarships |
| Amount | $3,720 (USD) |
| Organisation | University of Southern California |
| Department | International Hearing Aid Research Conference (IHCON) |
| Sector | Academic/University |
| Country | United States |
| Start | 07/2024 |
| End | 08/2024 |
| Description | Towards multilingual audio-visual speech enhancement in real noisy environments |
| Amount | £12,000 (GBP) |
| Organisation | The Royal Society |
| Sector | Charity/Non Profit |
| Country | United Kingdom |
| Start | 02/2023 |
| End | 02/2025 |
| Description | ULTRA-Earswitch: Tactical in-ear ultrasound driven headphones- communication/ biometrics/ noise protection and hands free control without reducing situational awareness: Awarded to Prof Mathini Sellathurai |
| Amount | £60,000 (GBP) |
| Funding ID | Contract Number: DSTLX1000169225 |
| Organisation | Defence Science & Technology Laboratory (DSTL) |
| Sector | Public |
| Country | United Kingdom |
| Start | 03/2022 |
| End | 08/2022 |
| Description | Unmute: Opening Spoken Language Interaction to the Currently Unheard |
| Amount | £970,668 (GBP) |
| Funding ID | EP/T024976/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 12/2020 |
| End | 11/2024 |
| Description | Unpacking the black box of interventions such as peer support designed to optimize mental health outcomes of family caregivers |
| Amount | £484,380 (GBP) |
| Funding ID | EP/X000788/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 08/2022 |
| End | 08/2024 |
| Title | Multi-modal Speech Enhancement Demonstrator Tool |
| Description | We developed the world's first open web-based demonstrator tool that shows how recordings of speech in noisy environments can be multi-modally processed to remove background noise and make the speech easier to hear. The demonstrator tool works for sound only, as well as video recordings, and enables researchers to develop innovative multi-modal speech and natural language communication applications. Users can listen to sample recordings and upload their own personal (noisy) videos or audio files to hear the difference after audio-visual processing using a deep neural network model. No uploaded data is stored. User data is erased as soon as the web page is refreshed or closed. |
| Type Of Material | Improvements to research infrastructure |
| Year Produced | 2023 |
| Provided To Others? | Yes |
| Impact | This innovative demonstrator tool was showcased at an international workshop organised as part of the 2022 IEEE Engineering in Medicine and Biology Society Conference (EMBC) in Glasgow, 11-15 July. Around 40 Workshop participants (including clinical, academic and industry researchers) were provided with an interactive hands-on demonstration of the audio-visual speech enhancement tool. The tool demonstrated, for the first time, the technical feasibility of developing audio-visual algorithms that can enhance speech quality and intelligibility, with the aid of video input and low-latency combination of audio and visual speech information. This served to educate participants and demonstrated the potential of such transformative tools to extract salient information from the pattern of the speaker's lip movements and to contextually employ this information as an additional input to speech enhancement algorithms, in future multi-modal communications and hearing assistive technology applications. |
| URL | https://demo.cogmhear.org/ |
| Title | Second COG-MHEAR International Audio-Visual Speech Enhancement Challenge (AVSEC-2): New baseline Deep Neural Network Model, Real-world Datasets and Audio-visual Intelligibility Testing Method |
| Description | We organised the second COG-MHEAR international AVSEC-2 Challenge that featured as an approved Challenge at IEEE ASRU 2023, 16-20 Dec 2023. As part of AVSEC-2, we developed and made openly available a new benchmark pre-trained deep neural network model and real-world (TED video) datasets. We further refined our method for evaluating audio-visual speech enhancement systems at scale using a fully validated keyword-spotting design that was presented at ICASSP 2023 (https://ieeexplore.ieee.org/document/10096479). |
| Type Of Material | Improvements to research infrastructure |
| Year Produced | 2023 |
| Provided To Others? | Yes |
| Impact | The Challenge has provided excellent advocacy for COG-MHEAR, bringing opportunities to strengthen the audio-visual speech enhancement (AV SE) community and bring together interdisciplinary researchers to work towards improving future natural language speech and hearing technologies. AVSEC-2 received a higher number of submissions compared to the first challenge, and we were pleased to see high-profile companies such as Mitsubishi among the participants. Moreover, there was an increase in performance of the best performing systems for multimodal speech-in-noise processing. The data produced from the challenge has enabled us to gain further understanding about the role that features of the audio and visual components play in intelligibility; we also investigated how intelligibility is affected when audio-only and audio-visual stimuli are presented, leading to important findings about the efficacy of speech enhancement in in-person settings. Our teams developed a new baseline pre-trained deep neural network model and made this openly available to participants, along with raw and pre-processed audio-visual datasets - derived from real-world TED talk videos - for training and development of new audio-visual models to perform speech enhancement and speaker separation at signal to noise (SNR) levels that were significantly more challenging than typically used in audio-only scenarios. The Challenge evaluation utilised established objective measures (such as STOI and PESQ, for which scripts were provided to participants) as well as a new audio-visual intelligibility testing method developed by the COG-MHEAR teams for subjective evaluation with human subjects. The latter was further refined as part of AVSEC-2 for evaluating AV SE systems at scale using a fully validated keyword-spotting design that was presented at ICASSP 2023. The new baseline model, real-world datasets and subjective audio-visual intelligibility testing method are continuing to be exploited by researchers in speech and natural language communication and hearing assistive technology applications. |
| URL | https://challenge.cogmhear.org/#/avsec2/ |
| Title | Third COG-MHEAR International Audio-Visual Speech Enhancement Challenge (AVSEC-3): New baseline Deep Neural Network Model, Real-world Datasets and Audio-visual Intelligibility Testing Method |
| Description | We organised the second COG-MHEAR international AVSEC-3 Challenge that featured as an approved Challenge. As part of AVSEC-3, we developed and made openly available a new benchmark pre-trained deep neural network model and real-world (TED video) datasets. |
| Type Of Material | Improvements to research infrastructure |
| Year Produced | 2024 |
| Provided To Others? | Yes |
| Impact | The Challenge has provided excellent advocacy for COG-MHEAR, bringing opportunities to strengthen the audio-visual speech enhancement (AV SE) community and bring together interdisciplinary researchers to work towards improving future natural language speech and hearing technologies. AVSEC-3 received a higher number of submissions compared to the first two challenges, and we were pleased to see high-profile companies. Moreover, there was an increase in performance of the best performing systems for multimodal speech-in-noise processing. The data produced from the challenge has enabled us to gain further understanding about the role that features of the audio and visual components play in intelligibility; we also investigated how intelligibility is affected when audio-only and audio-visual stimuli are presented, leading to important findings about the efficacy of speech enhancement in in-person settings. Our teams developed a new baseline pre-trained deep neural network model and made this openly available to participants, along with raw and pre-processed audio-visual datasets - derived from real-world TED talk videos - for training and development of new audio-visual models to perform speech enhancement and speaker separation at signal to noise (SNR) levels that were significantly more challenging than typically used in audio-only scenarios. The Challenge evaluation utilised established objective measures (such as STOI and PESQ, for which scripts were provided to participants) as well as a new audio-visual intelligibility testing method developed by the COG-MHEAR teams for subjective evaluation with human subjects. The latter was further refined as part of AVSEC-3 for evaluating AV SE systems at scale using a fully validated keyword-spotting design that was presented at Interspeech 2024. The new baseline model, real-world datasets and subjective audio-visual intelligibility testing method are continuing to be exploited by researchers in speech and natural language communication and hearing assistive technology applications. Accepted AVSEC-3 Workshop papers were published in ISCA Proceedings. Authors of selected papers (including winners and runner-ups of each Challenge Track) were invited to submit significantly extended papers for consideration in a Special Issue of the IEEE Journal of Selected Topics in Signal Processing (JSTSP). |
| URL | https://challenge.cogmhear.org/#/avsec3/ |
| Title | World's first large-scale Audio-Visual Speech Enhancement Challenge (AVSEC): New baseline Deep Neural Network Model, Real-world Datasets and Audio-visual Intelligibility Testing Method |
| Description | We developed and made openly available, a new benchmark pre-trained deep neural network model, real-world (TED video) datasets and a novel subjectve audio-visual intelligibility evaluation method as part of the world's first large-scale Audio-Visual Speech Enhancement Challenge. Details of the benchmark model, datasets and intelligibility testing method were published in peer-reviewed proceedings of the 2023 IEEE Spoken Language Technology (SLT) Workshop (https://ieeexplore.ieee.org/abstract/document/10023284). |
| Type Of Material | Improvements to research infrastructure |
| Year Produced | 2022 |
| Provided To Others? | Yes |
| Impact | The new benchmark pre-trained model code and training and evaluation datasets were made openly available as part of the world's first large-scale Audio-Visual Speech Enhancement (AVSE) Challenge organised by our COG-MHEAR teams as part of the 2023 IEEE Spoken Language Technology (SLT) Workshop, Qatar, 9-12 January 2023. The Challenge brought together wider computer vision, hearing and speech research communities from academia and industry to explore novel approaches to multimodal speech-in-noise processing. Our teams developed a new baseline pre-trained deep neural network model and made this openly available to participants, along with raw and pre-processed audio-visual datasets - derived from real-world TED talk videos - for training and development of new audio-visual models to perform speech enhancement and speaker separation at signal to noise (SNR) levels that were significantly more challenging than typically used in audio-only scenarios. The Challenge evaluation utilised established objective measures (such as STOI and PESQ, for which scripts were provided to participants) as well as a new audio-visual intelligibility testing method developed by the COG-MHEAR teams for subjective evaluation with human subjects. The new baseline model, real-world datasets and subjective audio-visual intelligibility testing method are continuing to be exploited by researchers in speech and natural language communication and hearing assistive technology applications. |
| URL | https://challenge.cogmhear.org/#/download |
| Title | 5G-Enabled Contactless Multi-User Presence and Activity Detection for Independent Assisted Living |
| Description | The dataset represents a combination of activities captured through wireless channel state information, using two USRP X300/X310 devices, to serve a system that was designed to detect presence and activities amongst multiple subjects. The dataset was divided into 16 classes, each represents a particular number of subjects and activities. More details can be found in the readme file. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2021 |
| Provided To Others? | Yes |
| Impact | This benchmark dataset has enabled the COG-MHEAR team to develop and evaluate a new-generation contactless 5G-based radio-frequency (RF) sensing system to detect the presence and activities of multiple persons. The developed system operates in the 5G frequency band (3.75 GHz) and has demonstrated significant potential to estimate the environmental context. This complements audio-visual (AV) speech enhancement research being conducted in COG-MHEAR by enabling environmental context estimation in a privacy-preserving manner. |
| URL | http://researchdata.gla.ac.uk/id/eprint/1151 |
| Title | AVSEC Challenge |
| Description | The aim of Audio-Visual Speech Enhancement (AVSE) Challenges is to bring together the wider computer vision, hearing and speech research communities to explore novel approaches to multimodal speech-in-noise processing. |
| Type Of Material | Data analysis technique |
| Year Produced | 2022 |
| Provided To Others? | Yes |
| Impact | Ongoing interest, with entrants from industry and academia taking part in each version of the challenge. |
| URL | https://challenge.cogmhear.org/#/docs |
| Title | COG-MHEAR Automatic Noise Removal Demo |
| Description | Off-chip Cloud based AV Hearing Aid speech enhancement using a new lightweight benchmark AV Speech Enhancement model |
| Type Of Material | Computer model/algorithm |
| Year Produced | 2022 |
| Provided To Others? | Yes |
| Impact | Discussion with the hearing sciences community; with hearing aid users; and with charity partners |
| URL | https://cogmhear.org/demo.html |
| Title | COG-MHEAR IoT (Internet-of-Things) Transceiver Demo |
| Description | A video demonstrating a first-of-its-kind prototype of a 5G Internet of Things (IoT) enabled hearing-aid. In the demo, the universal software radio peripheral (USRP) on the left, acts as an IoT device (hearing aid), and the USRP on the right, acts as an access point/base station and server for Cloud-based implementation of machine learning algorithms. The channel between the left IoT device to the access point is termed as an uplink channel and the channel between the access point and the IoT device is termed as a downlink channel. To enable real-time communication of audio-visual (AV) information from the IoT device to the access point, the uplink channel supports varying data-rates and hence utilises a long-term evolution (LTE) based modified frame structure developed for uplink data transmission. This supports 1.4 MHz and 3 MHz bandwidth with different modulation and code-rates for error correction codes. On the other hand, the access point only transmits audio information to the IoT device and hence supports a fixed data rate, by utilising an LTE-based modified frame structure with 1.4 MHz bandwidth. |
| Type Of Material | Computer model/algorithm |
| Year Produced | 2022 |
| Provided To Others? | Yes |
| Impact | Collaborative work between COG-MHEAR partners has led to successful integration and evaluation of our audio-based Minimal Viable Product (MVP) model with the 5G-IoT Transceiver prototype, as part of an initial real-time Cloud-based AV speech enhancement framework. The IoT transceiver has also been effectively integrated with novel chaos-based lightweight encryption schemes, further demonstrating its potential for implementing future privacy-preserving multi-modal hearing aids. |
| URL | https://vimeo.com/675527544 |
| Title | Intelligent Wireless Walls for Contactless In-Home Monitoring |
| Description | The dataset is about monitoring human activities in complex Non-line-of-sight (Non-LOS) environments. Radio frequency (RF) sensing was employed in particular to collect unique channel fluctuations induced by multiple activities. The data collection hardware consists of two USRP devices one used as a transmitter (Tx) and one as receiver (Rx). Both USRPs are placed in a position where Tx and Rx were not in LOS. One was corner scenario, and the other was multifloor scenario. In the corner scenario, Tx was in one corridor while the Rx was in the other corridor and reflecting intelligent surface (RIS) was placed at corner to steer the beam towards the subject. The activities were performed between Tx and RIS. In multifloor scenario, Tx was on 5th floor and Rx was 3rd floor along with RIS. Activities were performed between RIS and Rx. Two subjects participated in experiments where each activity was performed for 6 seconds. The considered activities were sitting, standing, walking and empty. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2022 |
| Provided To Others? | Yes |
| Impact | An important development in monitoring of human activity using RF. |
| URL | http://researchdata.gla.ac.uk/id/eprint/1281 |
| Title | Intelligibility-Oriented Audio-Visual Speech Enhancement model |
| Description | A first-of-its-kind intelligibility-oriented deep neural network-based model has been developed for audio-visual (AV) speech enhancement. Model codes and datasets have been made available via the COG-MHEAR website to serve as a benchmark resource for the research community. |
| Type Of Material | Computer model/algorithm |
| Year Produced | 2021 |
| Provided To Others? | Yes |
| Impact | Our innovative AV speech enhancement model and dataset have been made publicly available for benchmark evaluation by the research community. The model was presented at the EPSRC Clarity Workshop (16-17 Sep 2021) and also disseminated via Youtube: https://www.youtube.com/watch?v=2XU-OpfIlxY&list=PLNqx4n2qXsY_22KVZFoy9LxT6_ssxfSAS?dex=16 The interactive Workshop presentation stimulated lively discussions afterwards, with some participants requesting more information, and others expressing an interest to exploit our innovative intelligibility-oriented AV processing approach in their respective research and industry-led projects and activities. Plans for new collaborations were also discussed with some participants. |
| URL | https://github.com/cogmhear |
| Title | Interactive COG-MHEAR AV (Audio-Visual) MVP (Minimum Viable Product) Demonstrator |
| Description | Demonstration of an initial laptop-based minimum viable product (MVP) of our multi-modal speech enhancement technology being developed in the COG-MHEAR research programme. This first-of-its-kind interactive prototype operates in real-time in constrained web-based video conferencing environments, using both audio-only and audio-visual (lip-reading) modalities as part of a low-latency, context-aware AV speech enhancement framework. This can generalise to a range of visual and acoustic noises by addressing the practical issues of visual imperfections in real environments. |
| Type Of Material | Computer model/algorithm |
| Year Produced | 2021 |
| Provided To Others? | Yes |
| Impact | The developed real-time audio-based and audio-visual (AV) MVP demonstrators were showcased at our industry and user-focused workshops organised in 2021 and also at our first annual multi-stakeholders workshop organised in Feb 2022. The workshops provided a forum to showcase the groundbreaking work conducted in our COG-MHEAR project, and attracted multi-disciplinary audiences including national and international academics, clinicians, hearing-aid users, industry experts and enduser organisations. The 'live' MVP demonstrations stimulated lively discussions afterwards, with some participants requesting more information. Others expressed an interest to exploit our context-aware multi-modal processing approaches in their respective academic and clinical research and industry-led projects and activities. Plans for new collaborations were discussed with some participants. The interactions between multi-disciplinary Workshop participants stimulated fresh ideas for new and complementary research directions in multi-modal hearing assistive technology. These included exploiting our wireless radio frequency (RF) and machine learning based privacy-preserving technology for british sign language detection and lip-reading in the presence of face masks. The MVPs have been made openly available to the research and enduser community via the COG-MHEAR website, to solicit further feedback from end-users for continuing development, evaluation and optimisation. |
| URL | http://demo.cogmhear.org |
| Title | Non-invasive Localization using Software-Defined Radios |
| Description | The dataset is about locating human activities in an office environment. Radio frequency (RF) sensing was employed in particular to collect unique channel fluctuations induced by multiple activities. The data collection hardware consists of two USRP devices that communicate with each other when activity takes place inside their coverage region. The USRPs are based on the National Instrument (NI) X310/X300 models, which are connected to two PCs by 1G Ethernet connections and have extended bandwidth daughterboard slots that cover DC-6 GHz and up to 120 MHz of baseband bandwidth. The two PCs were equipped with Intel(R) Core (TM) i7 7700.360 GHz processors, 16 GB RAM, and the Ubuntu 16.04 virtual operating system. For wireless communication, the USRPs were equipped with VERT2450 omnidirectional antennae. One participant performed in a room environment for the duration of the experiment, collecting 4300 samples for seven different activities in three zones and locations. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2022 |
| Provided To Others? | Yes |
| Impact | An important development in use of RF for location of human activities in an office environment. |
| URL | https://researchdata.gla.ac.uk/1283/ |
| Title | Pushing the Limits of Remote RF Sensing: Reading Lips Under Face Mask |
| Description | The dataset is about reading lips in a privacy preserving manner. In particular, radio frequency (RF) sensing was used to capture unique channel variation due to lip movements. USRP x300 was utilised equipped with the VERT2450 omnidirectional antenna and HyperLOG 7040 X used for reception and transmission respectively. Further, the same experiment was repeated with a Xethru UWB radar, where doppler frequency shifts due to lip movements are captured. We consider six classes for lip movements. Five vowels (a, e, i, o, u) and one empty class where lips were not moving. We are able to read lips even under face masks. Three subjects 1 male and 2 females participated in the experiments. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2022 |
| Provided To Others? | Yes |
| Impact | This is an important step in the ability to lip read whilst maintaining privacy and hygiene using RF. This data relates to a paper published in Nature Communications: Hameed, H., Usman, M., Tahir, A. et al. Pushing the limits of remote RF sensing by reading lips under the face mask. Nat Commun 13, 5168 (2022). https://doi.org/10.1038/s41467-022-32231-1 |
| URL | https://researchdata.gla.ac.uk/1282/ |
| Title | Real-time AV Speech Enhancement based Web Communications Demo |
| Description | Recording of Live Video Demo showcased at the 2022 IEEE Engineering in Medicine and Biology (EMBC) Workshop: 2 speakers communicating in real-time on MS Teams, physically based in two distant noisy Cafe locations within the EMBC Conference venue (SECC, Glasgow, UK) |
| Type Of Material | Computer model/algorithm |
| Year Produced | 2023 |
| Provided To Others? | No |
| Impact | https://cogmhear.org/demo.html |
| URL | https://cogmhear.org/demo.html |
| Title | State Space Modeling for Low complexity Audiovisual Speech Enhancement |
| Description | This approach incorporates a Selective State-Space Mechanism (SSM-AVSE) that dynamically processes temporal dependencies in both speech and visual streams, allowing for more efficient feature extraction and fusion. Unlike conventional transformer-based AVSE models that require extensive self-attention computations, our SSM-based design leverages linear recurrent operations, making it highly scalable for real-time inference. Model codes and datasets have been made available via the COG-MHEAR website to serve as a benchmark resource for the research community. |
| Type Of Material | Computer model/algorithm |
| Year Produced | 2025 |
| Provided To Others? | Yes |
| Impact | Audiovisual Speech Enhancement (AVSE) has shown significant promise in improving speech intelligibility in noisy environments by leveraging both auditory and visual cues. However, existing deep learning-based AVSE models often suffer from high computational complexity, limiting their deployment on real-time edge devices. To address this, this work has proposed a novel State Space Modeling (SSM) framework for Low-Complexity AVSE, which integrates efficient state-space representations to enhance speech while significantly reducing computational overhead. |
| URL | https://github.com/NasirSaleem/AVSE-Mamba |
| Title | Wi-Fi and Radar Fusion for Head Movement Sensing Through Walls Leveraging Deep Learning. [Data Collection] |
| Description | Hameed, H., Tahir, A., Usman, M., Jiang, Z., Lubna, , Abbas, H. , Naeem, R., Tie Jun, C., Imran, M. A. and Abbasi, Q. (2024) |
| Type Of Material | Database/Collection of data |
| Year Produced | 2024 |
| Provided To Others? | Yes |
| Impact | Dataset for future hearing aid devices |
| URL | https://www.gla.ac.uk/schools/engineering/staff/qammerabbasi/#researchdatasets,2024 |
| Description | COG-MHEAR industry partnership with Sonova |
| Organisation | Sonova |
| Country | United States |
| Sector | Private |
| PI Contribution | Proposed new directions in hearing assistive technology, including the ambitious development of truly cognitively-inspired, multimodal Hearing Aids. These will autonomously adapt to the nature and quality of their visual and acoustic environmental inputs, leading to enhanced intelligibility in noise, with potentially reduced listening effort. Our overall goal is to collaborative develop, test and clinically evaluate real-time, personalised privacy-preserving audio-visual hearing-aid prototypes, including hardware and software implementations. |
| Collaborator Contribution | Providing access to industry experts, end-users and focus groups, and advising on the commercial relevance and feasibility of innovative hearing technology being developed in the COG-MHEAR research programme. Also contributing to each work package, while also providing a route to impact by benchmarking our multi-modal prototypes with commercial hearing-aid functionality, throughout all design, development and evaluation stages. |
| Impact | Three industry-led workshops were organised in 2021. Two of these were attended by multiple stakeholders from the COG-MHEAR user group comprising hearing-aid manufacturers, clinicians and enduser organisations, in addition to the COG-MHEAR research team including computer scientists, wireless and communications engineers, speech processing and hearing science researchers. The multi-disciplinary collaborations have enabled COG-MHEAR researchers to learn from industry experts and work closely with endusers to holistically address a full range of technical, privacy and usability challenges related to user-led co-design, evaluation and commercialization of future multi-modal hearing technology. The engagements have further led to identification of applications beyond hearing-aids that could benefit from related COG-MHEAR technology, such as novel multimodal ecological momentary assessment tools to transform existing sparse, unimodal commercial systems used by Sonova. These could enable the personalisation of design and usability of other medical instruments to enhance personal product experience. Further workshops in 2022 involved representatives from Sonova in user group discussions, as well as key advice from Sonova about development of the COG-MHEAR minimum viable product. This includes a workshop on 5 August 2022 (2 - 4pm) held with Dr Peter Derleth of Sonova, for expert feedback on scaling up our real-time Minimum Viable Product demonstrator. A visit to the Sonova labs is also planned to connect the ENU team with Sonova's AI team to pursue collaborative research discussions. A two-day in-person workshop with Dr Peter Derleth of Sonova, on 17-18 August 2023, ensuring that ongoing research is relevant to the hearing aid industry. During the workshop, Dr Derleth gave an interactive talk on careers in hearing assistive technology to COG-MHEAR researchers and PhD students. This Workshop led to a visit by ENU researchers to Sonova Labs and ongoing discussions for a new Sonova funded PhD studentship. |
| Start Year | 2021 |
| Description | Dr Cosimo Ieracitano and Prof Carlo Morabito |
| Organisation | University of Reggio Calabria |
| Country | Italy |
| Sector | Academic/University |
| PI Contribution | Collaboratively explored new explainable deep neural network (DNN) based approaches to inform audio-visual speech enhancement research as part of workpackage (WP) 1. |
| Collaborator Contribution | Complementary expertise in development of explainable multi-modal DNNs. |
| Impact | One jointly-authored research paper has resulted from the collaboration to-date, as part of Workpackage (WP) 1 of our COG-MHEAR research programme: Ieracitano, C., Mammone, N., Hussain, A. Morabito F.C,. A novel explainable machine learning approach for EEG-based brain-computer interface systems. Neural Comput & Applic (2021). https://doi.org/10.1007/s00521-020-05624-w |
| Start Year | 2021 |
| Description | Dr Faiyaz Doctor |
| Organisation | University of Essex |
| Country | United Kingdom |
| PI Contribution | Hosted a talk by Dr Faiyaz Doctor, giving details of his work on Fuzzy Systems. |
| Collaborator Contribution | Dr Faiyaz Doctor, School of Computer Science and Electronic Engineering at the University of Essex, gave a talk about fuzzy systems to the COG-MHEAR teams. This led to ongoing collaborations with the COG-MHEAR team which is exploiting fuzzy logic to learn the environment and user context and enhance interpretability of deep neural network based audio-visual speech enhancement models. |
| Impact | Ongoing |
| Start Year | 2022 |
| Description | Dr Jack Holman |
| Organisation | Glasgow Royal Infirmary |
| Country | United Kingdom |
| Sector | Hospitals |
| PI Contribution | A need to understand the nuances of listening effort and fatigue in order to develop emotion detection in multi-modal hearing aids. |
| Collaborator Contribution | A talk to COG-MHEAR teams: 'Listening effort and listening fatigue when speaking in noisy environments'. |
| Impact | A blog about the talk |
| Start Year | 2023 |
| Description | Dr Robert Adam, Heriot-Watt University |
| Organisation | Heriot-Watt University |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Dr Robert Adam, Associate Professor in Linguistics, Interpreting, BSL and Deaf Studies at Heriot Watt University, gave an invited talk at the COG-MHEAR Workshop about deaf culture and history. This led to follow-on collaborative research discussions on deaf people's interactions through and with technologies, including new networking opportunities with the Signs Group at HWU, which includes deaf and hearing researchers from the UK, Belgium, Denmark, Finland, India, Norway, Australia and the US. |
| Collaborator Contribution | Dr Robert Adam, Lecturer in Linguistics, Interpreting, BSL and Deaf Studies at Heriot Watt University, who gave a talk about deaf culture and history. His experience and insights as a deaf academic, particaulrly in the area of technology use, are helpful to the COG-MHEAR research programme. |
| Impact | Ongoing. |
| Start Year | 2023 |
| Description | Dr Simone Scardapane |
| Organisation | Sapienza University of Rome |
| Country | Italy |
| Sector | Academic/University |
| PI Contribution | Collaboratively explored the challenge of addressing fairness with graph representation learning, as part of workpackage (WP) 1 of our COG-MHEAR research programme. |
| Collaborator Contribution | Complementary expertise in fair and interpretable artificial intelligence (AI) models, led to the collaborative development of a novel approach to distributed "fairer" models, in the form of a biased data augmentation technique that modifies the training data to reduce the predictability of its sensitive attributes. |
| Impact | One jointly-authored research paper has resulted from the collaboration to-date, as part of WP 1 of our COG-MHEAR research programme: I. Spinelli, S. Scardapane, A. Hussain and A. Uncini, "FairDrop: Biased Edge Dropout for Enhancing Fairness in Graph Representation Learning," in IEEE Transactions on Artificial Intelligence, doi: 10.1109/TAI.2021.3133818 (2021) |
| Start Year | 2021 |
| Description | Dr. Fazal E Wahab |
| Organisation | University of Science and Technology of China USTC |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Collaborative development of a real-time Edge-based Artificial Intelligence (AI) speech enhancement platform as part of workpackage (WP2) of the COG-MHEAR research programme. |
| Collaborator Contribution | Collaborative partners have contributed to real-time speech enhancement on edge devices by optimizing neural architectures with lightweight recurrent units, transformer modeling, and efficient attention mechanisms to reduce computational overhead. They have enabled hardware-specific adaptations through model quantization and integration with AI accelerators for low-latency inference. Additionally, their efforts in robust benchmarking, real-world testing, and cross-disciplinary innovations-such as frequency attention and hybrid convolutional-recurrent architectures-have enhanced speech clarity while minimizing computational complexity. |
| Impact | One jointly-authored research paper has resulted from the collaboration to-date, as part of WP 2 of our COG-MHEAR research programme: Wahab, Fazal E., Zhongfu Ye, Nasir Saleem, Rizwan Ullah, and Amir Hussain. "MA-Net: Resource-efficient multi-attentional network for end-to-end speech enhancement." Neurocomputing 619 (2025): 129150. https://doi.org/10.1016/j.neucom.2024.129150 Second paper is under review in IEEE Transactions on Consumer Electronics as part of WP 2 of our COG-MHEAR research programme: Wahab, Fazal E., Zhongfu Ye, Nasir Saleem, Rizwan Ullah, and Amir Hussain Efficient Real-Time Speech Enhancement Using Adaptive Deep Learning in Dynamic Acoustic Environments. |
| Start Year | 2024 |
| Description | Earswitch |
| Organisation | Earswitch Ltd |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | Ongoing discussions about the way in which the Earswitch technology could be used in multi-modal hearing technolgy. |
| Collaborator Contribution | A talk about his work, and ongoing discussions about further collaboration on use of the technolgy. |
| Impact | Ongoing. |
| Start Year | 2022 |
| Description | Enduser organisations |
| Organisation | Action on Hearing Loss |
| Country | United Kingdom |
| Sector | Charity/Non Profit |
| PI Contribution | Discussions on transformative hearing-assistive technology demonstrators being developed in COG-MHEAR. Participatory co-design with endusers is a central philosophy of our work programme, with the COG-MHEAR User Group continuously recruited to represent different stakeholder perspectives. This is essential for maximising usability and uptake prospects, and for understanding end-user privacy issues. |
| Collaborator Contribution | Proactive engagement and participation of end-users to shape the design, delivery, dissemination, implementation and impact of our research. Endusers feedback on acceptability has affected key design and technology choices - ranging from usability choices to privacy-preserving properties of algorithms deployed in our minimum-viable prototype demonstrator. This has enabled the consortium to identify and address potential usability barriers, for increased uptake of our envisaged technology. |
| Impact | Two user-led workshops were organised over the past year where our technology prototypes were also showcased. The interactive demonstrations and networking discussions enabled end-users to be involved in all stages of our research in a programme of participatory design in order to help meet end-user expectations and design specifications. Our clinical research partners provided advice on the experimental design and analysis aspects of prototype evaluation and our industrial partners provided technical support for benchmarking our new multi-modal prototypes with commercial hearing-aid functionality, throughout the development and validation stages. The user-led Workshops also suggested new practical applications and use cases to evaluate our developed prototypes for wireless sensing and multi-modal speech enhancement, including automatic speech recognition, privacy-preserved British Sign Language detection, lip-reading in the presence of face-masks, human health and activity monitoring, and therapeutic and diagnostic systems. These have led to successful pilot studies with findings being reported in research papers currently in preparation. |
| Start Year | 2021 |
| Description | IEEE UKRI Industry Applications Society (IAS) Chapter |
| Organisation | IEEE Industry Applications Society |
| Country | United States |
| Sector | Charity/Non Profit |
| PI Contribution | Prof Amir Hussain is the chair of the IEEE UKRI Industry Applications Society (IAS) Chapter |
| Collaborator Contribution | Sponsorship of the monthly COG-MHEAR workshops, plus provision of speakers and partners from industry. |
| Impact | - |
| Start Year | 2022 |
| Description | Institute for Integrated Micro and Nano Systems |
| Organisation | University of Edinburgh |
| Department | Institute for Integrated Micro and Nano Systems |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Ongoing discussions about the use of the Institute's technology and facilities. |
| Collaborator Contribution | Prof Adam Stokes, the Institute for Integrated Micro and Nano Systems, University of Edinburgh, gave a talk with details of the range of robots and associated technologies that are being developed. The Institute is also now a research partner. |
| Impact | Ongoing. |
| Start Year | 2022 |
| Description | Interdigital |
| Organisation | InterDigital |
| Department | InterDigital Europe |
| Country | United Kingdom |
| Sector | Private |
| PI Contribution | ETSI ISAC |
| Collaborator Contribution | Working on USEcase for ETSI ISAC |
| Impact | NA |
| Start Year | 2024 |
| Description | Poppy Welch: Privacy in Audio-Visual Hearing Aids |
| Organisation | University of Southampton |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Invited Poppy Welch to give a talk to the COG-MHEAR teams about the importance of privacy in audio-visual hearing aids. |
| Collaborator Contribution | Poppy Welch gave a talk and entered discussions about privacy in relation to the developing audio-visual technology. |
| Impact | Still active. |
| Start Year | 2024 |
| Description | Privacy in Audio-Visual Hearing Aids |
| Organisation | University of Southampton |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | The COG-MHEAR teams invited Poppy Welch of the University of Southampton to give a talk on privacy when using audio-visual hearing aids. |
| Collaborator Contribution | Poppy Welch gave a talk and discussed privacy issues GDPR to the particular privacy concerns that will need to be addressed when using cameras to video people speaking, for audio-visual speech enhancement. |
| Impact | Ongoing discussions |
| Start Year | 2024 |
| Description | Prof Ashiq Anjum and Prof Huiyu Zhou |
| Organisation | University of Leicester |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Collaborative development of a real-time Edge-based Artificial Intelligence (AI) platform as part of workpackage (WP) 2 of our COG-MHEAR research programme. |
| Collaborator Contribution | Collaborative PhD project has led to the development of an innovative Cloud-based video analytics system using orientation fusion and convolutional neural networks for scalable object recognition. This has demonstrated significantly improved visual recognition accuracy under challenging conditions. This has informed ongoing work in WP2 of our research programme. |
| Impact | One jointly-authored research paper has resulted from the collaboration to-date, as part of WP 2 of our COG-MHEAR research programme: Yaseen M.U, Anjum A, Fortino G, Liotta A, Hussain A, Cloud based scalable object recognition from video streams using orientation fusion and convolutional neural networks, Pattern Recognition, Volume 121, Jan 2022, https://doi.org/10.1016/j.patcog.2021.108207. |
| Start Year | 2021 |
| Description | Prof Bin Luo |
| Organisation | Anhui University |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Collaborative work exploring computer vision approaches to more effectively extract and track visual features as part of WorkPackage (WP) 1 of our research programme. |
| Collaborator Contribution | Complementary expertise in attribute-guided deep neural architectures and enhanced deep neural networks for visual tracking. |
| Impact | Two jointly-authored research papers have resulted from the collaboration to-date, complementing Workpackage (WP) 1 of our CO-MHEAR research programme. Specifically: (i) Collaborative formulation of an attribute-guided deep neural architecture to address object re-identification challenges arising from large intra-class variation caused by view variations and illumination changes, and inter-class similarity [1]. [1] Li H., Lin X, Zheng A, Li C; Luo B; He R; Hussain A, "Attributes Guided Feature Learning for Vehicle Re-Identification," in IEEE Transactions on Emerging Topics in Computational Intelligence, (2021) doi: 10.1109/TETCI.2021.3127906. (ii) Collaborative development of an enhanced deep neural network (DNN) approach for visual tracking, termed the domain activation mapping guided network [2] addresses challenges of conventional DNN-based visual trackers being easily influenced by imbalanced background and foreground information in limited training samples. This informed audio-visual speech enhancement work in WP1. [2] Tu Z, Zhou A, Gan C, Jiang B, Hussain A, Luo B, A novel domain activation mapping-guided network (DA-GNT) for visual tracking, Neurocomputing, Volume 449, 2021, Pages 443-454, https://doi.org/10.1016/j.neucom.2021.03.05 |
| Start Year | 2021 |
| Description | Prof Hui Yu |
| Organisation | University of Portsmouth |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Follow-on discussions, impacted/fed into the continuing review/development of our Minimum Viable Product Roadmap |
| Collaborator Contribution | A talk about relevant aspects of Prof Hui Yu's research given to the COG-MHEAR and NATGEN teams, explaining advances in immersive and augmented reality, especially emotion sensing and portrayal. |
| Impact | Ongoing |
| Start Year | 2022 |
| Description | Prof João Paulo Papa |
| Organisation | Sao Paulo State University |
| Country | Brazil |
| Sector | Academic/University |
| PI Contribution | Collaborative pioneering work on development of low-energy cortical graph neural-networks for multi-modal speech enhancement. |
| Collaborator Contribution | Provided complementary expertise to evaluate the robustness of novel low-energy cortical graphical models with potential for on-chip hearing-aid implementation. |
| Impact | Jointly-authored research paper submitted to a peer-reviewed journal (pre-print available at: https://arxiv.org/pdf/2202.04528.pdf) |
| Start Year | 2021 |
| Description | Prof Kaizhu Huang |
| Organisation | Duke Kunshan University |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Collaboratively explored enhancements to address training, optimisation and generalisation capabilities of deep neural network (DNN) models to inform the development of an innovative real-time audio-visual (AV) speech enhancement framework as part of workpackage (WP) 1 of our COG-MHEAR research programme. |
| Collaborator Contribution | Complementary expertise in utilising latent distributions to enhance generative adversarial networks (GANs) and formulation of generalised zero-shot learning methods for low-latency audio-visual (AV) speech enhancement. This informed the development of our real-time audio-visual (AV) minimum viable product (MVP) demonstrator as part of WP1. |
| Impact | Three jointly-authored research papers have resulted from the collaboration to-date, complementing Workpackage (WP) 1 of our CO-MHEAR research programme. Specifically: (i) Simple latent distributions to enhance GANs [1]. [1] Zhang, S., Huang, K., Qian, Z. Hussain, A. Improving generative adversarial networks with simple latent distributions. Neural Comput & Applic 33, 13193-13203 (2021). https://doi.org/10.1007/s00521-021-05946-3 (ii) An artificial immune networks-based approach [2] is to optimise machine learning models [2] [2] Kanwal S, Hussain A, Huang K, Novel Artificial Immune Networks-based optimization of shallow machine learning (ML) classifiers, Expert Systems with Applications, Volume 165, 2021 https://doi.org/10.1016/j.eswa.2020.113834 (iii) To address practical challenges of limited availability of labelled image samples, as well as overfitting issues with conventional zero-shot learning (ZSL) methods, a coarse-grained generalised ZSL method developed with a self-focus mechanism, specifically, a focus-ratio that introduces the importance of each dimension into the model optimization process [3]. [3] Yang G, Huang K, Zhang R, Goulermas J.Y, Hussain A, Coarse-grained generalised zero-shot learning with efficient self-focus mechanism, Neurocomputing, Volume 463, 2021, Pages 400-410, https://doi.org/10.1016/j.neucom.2021.08.027. |
| Start Year | 2021 |
| Description | Prof Naomi Harte, Trinity College, Dublin |
| Organisation | Trinity College Dublin |
| Department | Department of Electronic & Electrical Engineering |
| Country | Ireland |
| Sector | Academic/University |
| PI Contribution | Need to build on Prof Harte's teams expertise in collecting speech corpora |
| Collaborator Contribution | Professor Naomi Harte of Trinity College Dublin described her work on speech recognition and recording, in a talk to the COG-MHEAR teams. This is documented in a blog: https://blog.cogmhear.org/multimodal-speech-and-collection |
| Impact | Ongoing communication about corpus collection. |
| Start Year | 2023 |
| Description | Prof Wenwu Wang |
| Organisation | University of Surrey |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Invited Prof Wenwu Wang to give a talk on his work on speech source separation with the COG-MHEAR teams. |
| Collaborator Contribution | COG-MHEAR team members asked Prof Wenwu Wang for further details about speech source separation to assist with their ongoing research. |
| Impact | Ongoing discussions with the COG-MHEAR teams |
| Start Year | 2024 |
| Description | Prof Yu Tsao |
| Organisation | Academia Sinica |
| Country | Taiwan, Province of China |
| Sector | Academic/University |
| PI Contribution | Collaboratively explored ideas for development and multi-lingual of a real-time framework based on deep neural network models for audio-visual speech enhancement, as part of workpackage (WP) 1 of our COG-MHEAR research programme. |
| Collaborator Contribution | Complementary expertise in multi-modal speech processing led to the collaborative development of a novel deep neural network model integrating local and global attention, with promising audio-based speech enhancement results. |
| Impact | The ongoing collaboration has led to successful joint-research bids (see Further Grants section) and jointly-authored research papers (as part of WP1 of our COG-MHEAR research programme). For example, see joint papers below: I. -C. Chern, K-H Hung; Y-T Chen; T. Hussain; M. Gogate; A. Hussain; Y. Tsao, J-C Hou (2023), "Audio-Visual Speech Enhancement and Separation by Utilizing Multi-Modal Self-Supervised Embeddings," 2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW), Rhodes, Greece, 2023, pp. 1-5, doi: 10.1109/ICASSPW59220.2023.10193049 J Kirton-Wingate, S Ahmed, M Gogate, Y Tsao, A Hussain (2023), Towards Individualised Speech Enhancement: An SNR Preference Learning System for Multi-Modal Hearing Aids, 2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW), Pages 1-5 |
| Start Year | 2021 |
| Description | Professor Aihua Zheng of Anhui University, China |
| Organisation | Anhui University |
| Country | China |
| Sector | Academic/University |
| PI Contribution | Queries about the way in which Prof Zheng's research could assist in COG-MHEAR research developments. |
| Collaborator Contribution | A talk about Prof Zheng's work to identify the same people and objects in images from different cameras; and about audio-matching: the ability to match voice and face from different video and photos |
| Impact | A blog on the COG-MHEAR website, plus ongoing discussions with Prof Zheng about collaboration opportunities. |
| Start Year | 2023 |
| Description | Signs at Heriot-Watt University |
| Organisation | Heriot-Watt University |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Invited talk by Dr Robert Adam of Heriot-Watt University about deaf culture and history at the COG-MHEAR Workshop. |
| Collaborator Contribution | The invited talk by Dr Robert Adam led to proposed interaction on the Signs@HWU project: 'Deaf people's interactions through and with technologies (2023 - 2027). This has opened new networking opportunities with the Signs Group which includes deaf and hearing researchers from the UK, Belgium, Denmark, Finland, India, Norway, Australia and the US. |
| Impact | Project due to start in May 2023 |
| Start Year | 2023 |
| Description | The Collaborative Research Centre (CRC) Hearing Acoustics |
| Organisation | Carl von Ossietzky University of Oldenburg |
| Country | Germany |
| Sector | Academic/University |
| PI Contribution | COG-MHEAR researchers have visited Prof Volker Hohmann and colleagues at the Collaborative Research Centre (CRC) Hearing Acoustics at the University of Oldenburg, Germany to exchange ideas about creation of ecologically-valid virtual conversational scenarios for use in designing and testing audio-visual speech enhancement models for future multimodal hearing technology. Prof Amir Hussain visited Prof Volker Hohmann's research group at Oldenburg University for further collaborative discussions on creation of ecologically-valid AV environments. The ongoing collaboration, supported by Sonova, aims to adapt the open TASCAR tool to create ecologically-valid virtual conversational environments with realistic AV avatars, particularly for evaluating future multimodal hearing aids. |
| Collaborator Contribution | An talk by Prof Hohmann to the COG-MHEAR teams about the unique lab setup and function, plus an invitation to visit the lab in person. |
| Impact | Ongoing. |
| Start Year | 2022 |
| Description | The EPSRC Clarity project organising audio-based Hearing Aid Challenges |
| Organisation | University of Nottingham |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | We collaborated with the EPSRC Clarity Challenge through Prof M. Akeroyd who is CI of both COG-MHEAR and the Clarity project. |
| Collaborator Contribution | Attendance and presentations at Workshop meetings. At the 2021 Clarity Challenge, we demonstrated a promising alternative to conventional (e.g. mean squared error based) cost functions, specifically, a first-of-its-kind 'intelligibility-oriented' deep neural network-based audio-visual (AV) speech enhancement model. This has underpinned our real-time AV minimum-viable product (MVP) demonstrator. |
| Impact | Conference paper: Hussain, T., Gogate, M., Dashtipour, K. and Hussain, A., 2021. Towards Intelligibility-Oriented Audio-Visual Speech Enhancement. in: The Clarity Workshop on Machine Learning Challenges for Hearing Aids (Clarity-2021) https://claritychallenge.github.io/clarity2021-workshop/papers/Clarity_2021_paper_hussain.pdf |
| Start Year | 2021 |
| Description | The Medical Devices Manufacturing Centre |
| Organisation | Heriot-Watt University |
| Department | Medical Device Manufacturing Centre (MDMC) |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Contributed to a further funding bid for the Centre. Ongoing proposals for use of the facilities. |
| Collaborator Contribution | Provision of local medical device manufacturing expertise and machinery that can be used to fabricate prototype hearing technology. |
| Impact | A talk by Prof Duncan Hand to the COG-MHEAR teams, showing a range of projects that have been carried out at the Medical Devices Manufacturing Centre. This resulted in COG-MHEAR contributing to a further funding bid for the Centre. |
| Start Year | 2022 |
| Description | The Microelectronics lab (meLAB) |
| Organisation | University of Glasgow |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Knowlege of the meLAB facilities and research can assist in the development of COG-MHEAR research, especially wearable and implantable technology. |
| Collaborator Contribution | Prof Hadi Heidari, Professor of Nanoelectronics and founder of the Microelectronics lab (meLAB), University of Glasgow described his group's work that includes surgical and wearable applications. |
| Impact | Ongoing |
| Start Year | 2022 |
| Title | Deep learning multi-user communication |
| Description | A one to many downlink system (e.g. wireless base-station 110 and user devices 120/130). The transmitter and receiver devices are each provided with a deep learning function 112/122/132 (e.g. a deep neural network, DNN) encoding and decoding user data. The deep learning functions are trained to optimise error free recovery of input data streams 101 at each user device 121 (the overall system essentially functions as an auto-encoder). The encoded data is subject to channel impairments 103/104 before being input to the decoder. The training may involve varying the channel impairment parameters (e.g. signal to noise ratio). Once trained the en/decoders are used to process live user data. An uplink version with a deep learning encoder per user device and a common base-station deep learning decoder is also claimed. |
| IP Reference | GB2602252 |
| Protection | Patent / Patent application |
| Year Protection Granted | 2022 |
| Licensed | No |
| Title | Real-time multimodal speech enhancement model, AI assisted audio-visual hearing aid |
| Description | A novel real-time multimodal speech enhancement model is developed for next-generation audio-visual hearing aids. |
| IP Reference | |
| Protection | Patent / Patent application |
| Year Protection Granted | 2024 |
| Licensed | Commercial In Confidence |
| Company Name | Rfiot Ltd |
| Description | |
| Year Established | 2023 |
| Impact | trials done in autonomous bus, crhicton trust and other places |
| Description | 13 June 2022: Mini Audio-Visual Hearing Aid workshop |
| Form Of Engagement Activity | A formal working group, expert panel or dialogue |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Professional Practitioners |
| Results and Impact | An audiologist who uses hearing aids took part in an online discussion with COG-MHEAR researchers. This gave key information on the practicalities of introducing new technology to hearing aid users; and indications of ways in which hardware should be developed to ensure maximum uptake. |
| Year(s) Of Engagement Activity | 2022 |
| URL | https://cogmhear.org/index.html |
| Description | 7 December 2022: Pilot in-person hearing aid user workshop |
| Form Of Engagement Activity | A formal working group, expert panel or dialogue |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Study participants or study members |
| Results and Impact | The COG-MHEAR teams showed their hardware and software developments to 3 hearing-aid users who attended in person. They gave their views about the main problems with their existing hearing technology. which helped in ensuring that the COG-MHEAR RESEARCH is developed in useful directions. They also gave feedback on the developing technology demonstrations. This was very useful in showing the researchers that various ways of interacting with the demonstrations are needed, depending on the preferences of each individual hearing aid user. |
| Year(s) Of Engagement Activity | 2022 |
| URL | https://blog.cogmhear.org/ |
| Description | Annual reviews |
| Form Of Engagement Activity | A formal working group, expert panel or dialogue |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Other audiences |
| Results and Impact | Annual review of COG-MHEAR research to gain feedback from stakeholders and the International Advisory Board. This ensures that experts in the field check the research progress and outcomes, and comment on the research direction for the coming year. |
| Year(s) Of Engagement Activity | 2022,2023,2024 |
| URL | https://blog.cogmhear.org/first-year-of-cogmhear-research |
| Description | Appointed to the Chair Panel of the UKRI Interdisciplinary Assessment College |
| Form Of Engagement Activity | A formal working group, expert panel or dialogue |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Other audiences |
| Results and Impact | Appointed to the Chair Panel of the UKRI Interdisciplinary Assessment College since 2022 |
| Year(s) Of Engagement Activity | 2022,2023,2024 |
| URL | https://engagementhub.ukri.org/ukri-talent/iac/ |
| Description | Appointed to the EPSRC Engineering Healthier Environments Expert Panel |
| Form Of Engagement Activity | A formal working group, expert panel or dialogue |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Other audiences |
| Results and Impact | Appointed to the EPSRC Engineering Healthier Environments Expert Panel |
| Year(s) Of Engagement Activity | 2024 |
| URL | https://www.ukri.org/opportunity/engineering-healthier-environments-micro-network-and-micro-network-... |
| Description | BSI/Innovate UK half-day online interactive Scoping Workshop |
| Form Of Engagement Activity | A formal working group, expert panel or dialogue |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Industry/Business |
| Results and Impact | This Workshop is part of the study into the development of a scope for a standard on radio frequency-based 1 to 5 metre low power transmission to wearable electronic devices, in support of the Standards Challenge Fund (SCF) programme. This virtual event will provide an opportunity to review an initial concept of a standard in this area and share ideas on the key common technical and other requirements and good practices needed in regards to the performance, design, testing and safety of the devices, their components, chargers and transmitters. The outputs from this discussion will help to inform BSI's recommendations and next steps for standards in this area. |
| Year(s) Of Engagement Activity | 2024 |
| URL | https://www.bsigroup.com/en-GB/products-and-services/standards-services/standards-challenge-fund/ |
| Description | Blog posts |
| Form Of Engagement Activity | Engagement focused website, blog or social media channel |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Patients, carers and/or patient groups |
| Results and Impact | A series of blogs were published to provide an informal and engaging means of updating visitors to the COG-MHEAR website. Initial blogs summarised key points from the main workshops held in the first year of the project. The @cogmhear Twitter account provided another channel for networking and disseminating our user-led events, monthly researcher workshops, and project publications. These provided further opportunities for engagement and participation to enable end-users of research and other stakeholders to shape its design, delivery, dissemination, implementation and impact. The published blogs and social media engagement led to requests on how COG-MHEAR technology can be harnessed by future hearing-aid end-users. Our COG-MHEAR researchers and collaborators reported increased interest in exploiting wireless and multi-modal processing in related subject areas, including automatic speech recognition, British Sign Language detection, human health and activity monitoring, and therapeutic and diagnostic systems. |
| Year(s) Of Engagement Activity | 2021,2022 |
| URL | https://blog.cogmhear.org/ |
| Description | Blogs about COG-MHEAR activities and speakers |
| Form Of Engagement Activity | Engagement focused website, blog or social media channel |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Public/other audiences |
| Results and Impact | A series of blogs were published to provide an informal and engaging means of updating visitors to the COG-MHEAR website. Initial blogs summarised key points from the main workshops held in the first year of the project. The series of blogs has developed with the addition of plain English blogs about talks given to the COG-MHEAR teams, as well as engagement activities. The LinkedIn channel: linkedin.com/in/cog-mhear-research-programme-55a016223 and @cogmhear X account provided other dissemination and networking channels for details of events, publications and opportunities to take part in the research. The published blogs and social media engagement led to requests on how COG-MHEAR technology can be harnessed by future endusers. Our COG-MHEAR researchers and collaborators also reported increased interest in exploiting wireless and multi-modal processing in related subject areas, including automatic speech recognition, British Sign Language detection, human health and activity monitoring, and therapeutic and diagnostic systems. |
| Year(s) Of Engagement Activity | 2022,2023,2024,2025 |
| URL | https://blog.cogmhear.org/blog |
| Description | COG-MHEAR website |
| Form Of Engagement Activity | Engagement focused website, blog or social media channel |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Other audiences |
| Results and Impact | Website to disseminate the COG-MHEAR research, including blogs. Reached around 200 people in the first year (March 2021-January 2022). |
| Year(s) Of Engagement Activity | 2021,2022 |
| URL | https://cogmhear.org/ |
| Description | COG-MHEAR's 3rd International AVSEC-3 Challenge |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | COG-MHEAR's 3rd International AVSEC-3 Challenge was organised as a Satellite Workshop at Interspeech 2024. This was a great success with a total of 22 papers accepted after a two-stage peer review process, which included submissions from AVSEC-1 and AVSEC-2 participants. The online ISCA-indexed AVSEC Workshop Proceedings are now available: https://www.isca-archive.org/avsec_2024/index.html |
| Year(s) Of Engagement Activity | 2024 |
| URL | https://www.isca-speech.org/event-5778746 |
| Description | First annual COG-MHEAR User Engagement Workshop |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Third sector organisations |
| Results and Impact | The aim of the workshop was to discuss the technology and consider how potential barriers to accepting the new hearing technology could be overcome; to develop privacy preserving models; and to explore public perceptions of the proposed hearing aid technology. |
| Year(s) Of Engagement Activity | 2021 |
| URL | https://blog.cogmhear.org/ |
| Description | Gaining opinion from audiologists on proposed audio-visual speech-in-noise tests |
| Form Of Engagement Activity | A formal working group, expert panel or dialogue |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Professional Practitioners |
| Results and Impact | An online workshop to find: What do audiologists (including audiologists who wear hearing aids) think about proposed audio-visual speech in noise (SIN) tests? a. Are the instructions explicit enough for patients to perform the test without clinical assistance? b. What clarifications would you propose adding to the test instructions if you believe they lack clarity? Feedback from an online meeting held on June 13, 2023, highlighted the need for clearer and simpler test instructions, along with ensuring awareness of the varying difficulty levels of the tests. |
| Year(s) Of Engagement Activity | 2023 |
| Description | General co-chair for the 14th International Brain Inspired Cognitive Systems (BICS) 2024 at Hefei, 6-8 Dec 2024 |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Other audiences |
| Results and Impact | General co-chair for the 14th International Brain Inspired Cognitive Systems (BICS) 2024 at Hefei, 6-8 Dec 2024 |
| Year(s) Of Engagement Activity | 2024 |
| Description | Hearing aid users testing the real-time audio-visual speech enhancement demonstration that has been developed by COG-MHEAR |
| Form Of Engagement Activity | A formal working group, expert panel or dialogue |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Study participants or study members |
| Results and Impact | How do hearing aid users find the experience of testing the real-time audio-visual speech enhancement demonstration that has been developed by COG-MHEAR? Insights from an in-person user workshop conducted on November 8, 2023, indicated that the technology notably improved speech clarity in noisy environments for all hearing aid users. Their feedback prompted enhancements to the tests, including: minimising unnecessary noise that quickly causes fatigue; simplifying questions; ensuring that future tests are 'double blind' for both talker whose voice is to be identified, and participant; and ensuring that participants are aware that some of the tests are very difficult. The findings are being summarised in a paper. |
| Year(s) Of Engagement Activity | 2023 |
| Description | Industry-centred Workshop |
| Form Of Engagement Activity | A formal working group, expert panel or dialogue |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Industry/Business |
| Results and Impact | Representatives from global hearing-aid manufacturers, Sonova provided key insights and recommendations on technical hearing-aid (HA) design and usability aspects, including listening with binaural HAs and the importance of information from both ears, as well as highlighting considerations for wireless information transmission. They also provided advice on clinical evaluation and the processes and challenges of moving from concept to market. An initial version of an audio-based minimum-viable product (MVP) demonstrator of our envisaged multi-modal HA and its future collaborative development plan was showcased by COG-MHEAR researchers for early feedback from industry experts and endusers. The presentations stimulated lively discussions afterwards, with some participants requesting more information, and others expressing an interest to exploit our innovative, contextual multi-modal processing approach in academic and industry-led projects and activities. Plans for new collaborations were also discussed with some participants. |
| Year(s) Of Engagement Activity | 2021 |
| URL | https://blog.cogmhear.org/ |
| Description | Invited Talk and research visit at Duke-Kunshan University, 8-9 Dec 2024 |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Postgraduate students |
| Results and Impact | Invited Talk and research visit at Duke-Kunshan University, 8-9 Dec 2024 |
| Year(s) Of Engagement Activity | 2024 |
| Description | Invited keynote at 11th International Conference on Computational and Experimental Science and Engineering (ICCESEN 2024) ICCESEN, Antalya, 25-28 October 2024 |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Other audiences |
| Results and Impact | Invited keynote at 11th International Conference on Computational and Experimental Science and Engineering (ICCESEN 2024) ICCESEN, Antalya, 25-28 October 2024 |
| Year(s) Of Engagement Activity | 2024 |
| URL | https://www.iccesen.org/ |
| Description | Invited keynote at 7th International Conference on Sustainable Sciences and Technology (ICSuSaT 2024), Istanbul, 12-14 July |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Other audiences |
| Results and Impact | Invited keynote at 7th International Conference on Sustainable Sciences and Technology (ICSuSaT 2024), Istanbul, 12-14 July |
| Year(s) Of Engagement Activity | 2024 |
| URL | https://icsusat.net/home |
| Description | Invited keynote at ICATH 2024, Salerno, Italy, 17-19 July 2024 |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Other audiences |
| Results and Impact | Invited keynote at ICATH 2024, Salerno, Italy, 17-19 July 2024 |
| Year(s) Of Engagement Activity | 2024 |
| URL | https://icath-conf.org/ |
| Description | Invited presentation to Advanced Materials in Medicine showcase, Manchester, UK |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Postgraduate students |
| Results and Impact | Invited presentation to Advanced Materials in Medicine showcase, Manchester, UK |
| Year(s) Of Engagement Activity | 2023 |
| Description | Invited presentation to International Centre for Translational Digital Health, UK / Canada / Melbourne. |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | Invited presentation to International Centre for Translational Digital Health, UK / Canada / Melbourne. |
| Year(s) Of Engagement Activity | 2023 |
| Description | Invited presentation to University of Cambridge, Department of Engineering |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Postgraduate students |
| Results and Impact | Invited presentation to University of Cambridge, Department of Engineering |
| Year(s) Of Engagement Activity | 2023 |
| Description | Invited talk in IWAT conference USA |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | Invited talk on Joint sensing and communication |
| Year(s) Of Engagement Activity | 2025 |
| Description | Invited talk and research visit at Academia Sinica, Taiwan, 10-12 December 2024 |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Postgraduate students |
| Results and Impact | Invited talk and research visit at Academia Sinica, Taiwan, 10-12 December 2024 |
| Year(s) Of Engagement Activity | 2024 |
| Description | Invited talks and research visits, Anhui University, UESTC, and Shanghai University, 18-23 May 2024 |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Postgraduate students |
| Results and Impact | Invited talks and research visits, Anhui University, UESTC, and Shanghai University, 18-23 May 2024 |
| Year(s) Of Engagement Activity | 2024 |
| Description | July 2022 EMBC Workshop |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Other audiences |
| Results and Impact | A workshop at the Engineering and Medicine and Biology Conference. This was a showcase for the range of COG-MHEAR work in progress, including a real-time multi-modal speech enhancement prototype that can exploit lip reading cues to effectively enhance speech in real noisy environments. |
| Year(s) Of Engagement Activity | 2022 |
| URL | https://blog.cogmhear.org/hearing-technology-showcase-embc-2022 |
| Description | Keynote in conference |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Postgraduate students |
| Results and Impact | keynote by Prof Abbasi in Fit conference Pakistan, https://fit.edu.pk/ |
| Year(s) Of Engagement Activity | 2024 |
| URL | https://fit.edu.pk/ |
| Description | Keynote in conference |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | Keynote on 6G by Prof Qammer Abbasi, IMAS, Morocco, https://imas2024.org/ |
| Year(s) Of Engagement Activity | 2024 |
| URL | https://imas2024.org/ |
| Description | Keynote talk |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | Keynote by Prof Abbasi in Connected Pakistan, Islamabad, https://connectedpakistan.pk/ |
| Year(s) Of Engagement Activity | 2024 |
| URL | https://connectedpakistan.pk/ |
| Description | Manchester epilepsy research network meeting |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Professional Practitioners |
| Results and Impact | Invited presentation to the Manchester epilepsy research network |
| Year(s) Of Engagement Activity | 2023 |
| Description | Multistakeholder workshop |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Other audiences |
| Results and Impact | Our first annual multi-stakeholder workshop was organized on 23 Feb 2022 which served as a multidisciplinary showcasing forum for our innovative COG-MHEAR research. The Workshop programme included keynote talks by the project PI and Work-Package Leads, an interactive poster session showcasing collaborative research by postdoctoral and doctoral researchers, and a real-time demonstration of our multi-modal minimum-viable product (MVP) operating in live web-based video conferencing environments. This gained appreciation from participants, including clinicians, end users and industry representatives, and leading national and international academics and researchers. The presentations stimulated lively discussions afterwards, with some participants requesting more information, and others expressing an interest to exploit our innovative, contextual multi-modal processing approach in their respective academic and clinical research and industry-led projects and activities. Plans for new collaborations were also discussed with some participants. |
| Year(s) Of Engagement Activity | 2022 |
| URL | https://cogmhear.org/ |
| Description | Presentation of COG-MHEAR work at an EPSRC Digital Health Policy Workshop |
| Form Of Engagement Activity | A formal working group, expert panel or dialogue |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Supporters |
| Results and Impact | Members of the COG-MHEAR teams attended an EPSRC Digital Health Policy Workshop to present their work, including: 1. Real-time audio visual speech enhancement software 2. Radar-based cognitive load sensor (which runs in real-time with a mini-analyzer) 3. Off-line version of the audio visual speech enhancement technology 3. 5G testbed demo video |
| Year(s) Of Engagement Activity | 2024 |
| Description | September 2022 UK Speech Workshop |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Other audiences |
| Results and Impact | Presenting at poster sessions during the 2022 UK Speech conference. This resulted in new contacts and collaborative opportunities with industry and academia. |
| Year(s) Of Engagement Activity | 2022 |
| URL | https://blog.cogmhear.org/blog |
| Description | Showcasing COG-MHEAR research at Oxford University and Oxford Science Enterprises |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Other audiences |
| Results and Impact | Prof Amir Hussain presented COG-MHEAR research at Oxford University and Oxford Science Enterprises |
| Year(s) Of Engagement Activity | 2024 |
| Description | Soapbox Science |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Public/other audiences |
| Results and Impact | Dr Bryony Buck and Prof Mathini Sellathurai stood on Soapboxes in the centre of Edinburgh and presented their research in plain English and answered questions from members of the public who were passing by. |
| Year(s) Of Engagement Activity | 2024 |
| URL | https://blog.cogmhear.org/blog/bbuck-soapbox-science |
| Description | Two shows at the Edinburgh Festival Fringe Cabaret of Dangerous Ideas |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Public/other audiences |
| Results and Impact | How will hearing aid users wear and use AV hearing assistive technology and how can a camera be worn as part of hearing assistive technology? During public engagement sessions at the Edinburgh Festival Fringe in August 2023, this particular question was addressed in two shows as part of the Cabaret of Dangerous Ideas presented by Dr Dorothy Hardy. These shows were conducted with simultaneous translation into British Sign Language (BSL) and were included in the Edinburgh Deaf Fest programme. The comedic presentation of the research, accompanied by large props, sparked numerous questions and discussions, and prompted new inquiries about the user group. |
| Year(s) Of Engagement Activity | 2023 |
| URL | https://blog.cogmhear.org/hearing-aids-dangerous-ideas |
| Description | Wearing audio-visual hearing aids: a workshop with audiologists, clinicians and an industry representative, most of whom were hearing aid users |
| Form Of Engagement Activity | A formal working group, expert panel or dialogue |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Professional Practitioners |
| Results and Impact | A discussion about the practicalities of wearing the multi-modal hearing aids that are being developed in the COG-MHEAR research programme. Most of the participants were hearing aid users. They were clinicians, audiologists and an industry representative. They joined the workshop remotely on Teams. They included clinicians and audiologists, plus an industry expert from Sonova. The wealth of expertise from their own and their client's use of hearing aids was evident and valuable. The suggestions and queries that arose have been important in focusing the research programme to ensure that privacy is preserved with the new hearing aids, and to address issues around wearability and usability. The results of the workshop were presented as a paper and poster at UK Speech 2022 on 6th September 2022 at the University of Edinburgh. |
| Year(s) Of Engagement Activity | 2022 |
| URL | https://cogmhear.org/ |
| Description | Workshop with Sonova |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Other audiences |
| Results and Impact | Interactive discussions on the ongoing development of a multi-modal hearing-aid prototype between industry partners at Sonova and the COG-MHEAR research team and user group members. Researchers took onboard expert advice and feedback from industry experts related to commercial hearing-aid design, evaluation and usability challenges. These informed the continuing development, optimisation and evaluation of our minimum-viable prototype (MVP) demonstrator that was showcased at the Workshop. Plans for a future hearing-aid enduser led workshop were also discussed and agreed. |
| Year(s) Of Engagement Activity | 2022 |
| Description | iCare Workshop, Calabria, Italy, 23-24 Nov 2023 |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Other audiences |
| Results and Impact | iCare Workshop, Calabria, Italy, 23-24 Nov 2023 |
| Year(s) Of Engagement Activity | 2023 |
| URL | https://www.icare-glu.com/program |