AI for Music in the Creative Industries of China and the UK

Lead Research Organisation: Queen Mary, University of London
Department Name: Sch of Electronic Eng & Computer Science

Abstract

Artificial Intelligence is changing in the Creative Industries from creation and production, protection, distribution, to consumption. The Music Industry is a leading example of a Creative Industry sector embracing AI, and its use of AI impacts and foreshadows other Creative Industries, providing a vibrant and rich ecosystem in which to examine the use and implications of AI. The size of the global Music Industry and the substantially different landscapes of digital music, AI, and culture between the UK and China provide significant opportunities for interdisciplinary long term collaboration building on each countries' different yet complementary strengths.

Two research-industry workshops will be held in London, UK, and Shanghai, China, to examine the increasing role and potential of AI for music in the Music Industry and the Creative Industries in China and the UK. The workshops will build partnerships leading directly to the development of future substantial collaborations between the UK and China in AI and music in the Creative Industries. To achieve this the workshops will map the current landscape of AI for music in the Creative Industries of UK and China, and examine questions including:
- What can be learnt from AI for music across Creative Industries;
- How data might be shared across sectors, countries, and cultures;
- How IP and business models are affected by AI;
- What skills are needed for AI in Creative Industries;
- How the impact of AI on Creative Industries might be measured.

Planned Impact

Bringing together researchers and industry stakeholders from the UK and China will provide state of the art insights into the current landscape for AI and music. This will provide context for answers to the remaining questions such as what can be learnt from AI for music in the Music Industry and other Creative Industries. The workshops will prioritise which remaining questions have the greatest potential for future partnerships and impact e.g. whether future partnerships would be in the ethics of AI and music, or new business models for AI, etc. This prioritisation of questions leads to prioritisation of which challenges are to be addressed, and which opportunities to be taken. For example, the question of how might large data sets be shared directly responds to the opportunity of sharing data to improve AI creativity, and would involve tackling the challenge in differing regulation and cultural contexts.

Publications

10 25 50
 
Description Through two workshops with professionals and researchers in the music sectors of China and the UK we found that both the context of music making and consumption, and the digital platforms used were divergent between the UK and China. We found more focus on amateur music creation in Chinese digital platforms (e.g. karaoke) compared to the UK, and more emphasis on professional music production technologies in the UK. Two key reasons for such differences include: i) the inherent bias of professional music production platforms to Western musical styles, and ii) the preference of mobile phones as the platform of choice for music consumption in China.
Exploitation Route The workshops highlighted that the rapid growth and acceptance of AI technologies in music making and consumption offer opportunities to explore support for the creation, access, and consumption of large data sets of Chinese and Western music and data on music consumption in radical yet culturally sensitive and responsive ways. For example, it may be possible to AI-based style-transfer techniques to support cross-cultural content creation, production and consumption, allowing us to bridge the gap between contemporary music technologies and Chinese music traditions. This may bring new life to Chinese traditional music through new technology, and foster greater access to Chinese music both in the UK and in China, especially for younger generations. And, we may be able use adaptive music techniques to reduce the barriers to creating Chinese music with contemporary music production tools and at the same time create new products and services at the intersection of Chinese and Western music.
Sectors Creative Economy,Digital/Communication/Information Technologies (including Software),Culture, Heritage, Museums and Collections

URL http://ai4music.eecs.qmul.ac.uk
 
Description The project brought together practitioners, researchers, and industry in AI for Music in the UK and China. This created new networks and collaborations which did not previously exist. Especially important are the new connections built in this project between the UK and China.
First Year Of Impact 2019
Sector Creative Economy,Digital/Communication/Information Technologies (including Software),Culture, Heritage, Museums and Collections
Impact Types Cultural,Economic

 
Description Networking with practitioners, researchers, and industry in AI for Music 
Organisation Tongji University
Country China 
Sector Academic/University 
PI Contribution Networking and hosting workshops
Collaborator Contribution Networking and hosting workshops
Impact Partnerships built between: Nick Bryan-Kinns Queen Mary University of London (UK) Justin Paterson University of West London (UK) Brad Cohen Tido Music (UK) Maurice Ashkenazi-Bakes MXX (UK) Johan Pauwels Queen Mary University of London (UK) Beici Liang Queen Mary University of London (UK) Benjamin Timms Steinberg (UK) Oliver Kadel 1618 Digital (UK) George Fazekas Queen Mary University of London (UK) Mileece i'anson Children of Wild (China/ UK) Rudy Wimmer CBI China Bridge (China) Zhou Chongling Tongji University (China) Qin Yi Shanghai Conservatory of Music (China) Xiaojing Liang China Conservatory of Music (China) Jan Dornig Tongji University (CDI) (China) Hua Dong Tongji University (China) Hui Zhang Zhejiang University (China) Zhao Yang BaroxTech (China) Benjamin Bacon Dogma Studio (China) Qi Mengjie Central Conservatory of Music (China) Cai Yuening Tongji University (Soundlab) (China) Liu Zhoa Tongji University (Soundlab) (China) Yinan Zhang Tongji University (Soundlab) (China) Qingying Zhu Ping An Technology (China) Yanqing Chen Alibaba (China) Kang Ming Zhan Shanghai Conservatory of Music (China) Peng Dong ACRCloud (China) Sun Xiaohua Tongji CDI (China) Aozhi Liu Ping An Technology (China) Yaluo Sun Sunny Media (China) Xiao Lu Tencent Music Entertainment Group (China) Roxy Crust Music (China) Junqi Deng Hangzhou Alibaba Music Technology Co., Ltd. (China) Jianzong Wang Ping An Technology - Deep Learning Team (China) Minwei Gu Tencent Music Entertainment Group (China) Yangzihao Wang Tencent - AI Platform (China) Rongfeng Zhu BaroxTech (China) Anthony Zhan Zera Culture Group (China) Yanqing CHEN Xiami Music of Alibaba Group (China) Yishu MAO Xiami Music of Alibaba Group (China) Yixi CHEN Xiami Music of Alibaba Group (China) Zhao Yang BaroxTech (China) Zijin Li China Conservatory of Music (China)
Start Year 2019
 
Description AI for Music in the Creative Industries of China and the UK Webite 
Form Of Engagement Activity Engagement focused website, blog or social media channel
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Website detailing the project and workshops, and including 10 minute video explainer.
Year(s) Of Engagement Activity 2019
URL http://ai4music.eecs.qmul.ac.uk
 
Description AI for Music in the Creative Industries of China and the UK: London Workshop 
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 AI is a key element of both UK and Chinese national strategies - the UKRI priority area Applications and Implications of AI includes Creative Industries, and AI is the first of four Grand Challenges identified by the UK Government's Industrial Strategy White Paper (2017). At the same time, the digital music market is now the largest segment of the global Music Industry, with a global revenue of $9.4bn, representing 54% of the industry's total revenue, predominantly due to innovative music technology SMEs, which represent 99% of all music businesses, and deliver 80% of all new music releases and 80% of the industry's jobs (IMPALA, 2019). The UK is a leader in Music Industries and one of the few countries which is a net exporter, providing an opportunity for UK-China collaboration building on the UK's strength in the sector and the rapidly changing Chinese sector which experienced 32% growth in digital music from 2016 to 2017.
This workshop brought together music practitioners, industry, and researchers from UK and China to:
- Map landscape of AI for Music in UK and China
-Build industry-research partnerships and UK-China partnerships
-Develop detailed funding proposal
Year(s) Of Engagement Activity 2019
URL http://ai4music.eecs.qmul.ac.uk/london-workshop/
 
Description AI for Music in the Creative Industries of China and the UK: Shanghai Workshop 
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 A China-UK research-industry partnering workshop was held from 15-17 April 2019 in Shanghai, China. Hosted by Tongji University in partnership with Queen Mary University of London.
Workshop participants identified 33 topics of interest in AI for Music in the Creative Industries of China and the UK from which two themes were developed during the workshop for future research proposals:
1. AI for Engaging Music: How can AI, HCI and multimedia make Chinese music more accessible and engaging to creative people in both China and the UK?
2. AI for Adapting Music: What are the opportunities for AI to adapt audio content and production to benefit audiences in both UK and China?
These two themes would bring together UK and Chinese researchers and industry to address challenges of music access, production, and consumption in China and the UK building on expertise from both countries.
Year(s) Of Engagement Activity 2019
URL http://ai4music.eecs.qmul.ac.uk/shanghai_april2019/
 
Description Talk on AI for Music at Design Driven Artificial Intelligence workshop, Tongji Uni, Shanghai, China 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Postgraduate students
Results and Impact A one-day forum was held on March 19th 2019, introducing the topic, showcasing ongoing projects and inviting you to talk about opportunities in this space.
The keynote was given by Prof. Gesche Joost, Head of the Design Research Lab at the Berlin University of the Arts and director of the research group "Interactive Textiles" at the German Research Center for Artificial Intelligence.
More speakers from companies such as SAP, Intel, Tencent, Huawei, IDEO and universities including Fudan University, NYU Shanghai, Xi'an Jiaotong-Liverpool, etc. have been invited to share.

The agenda for the day will be a mix of talks and discussions to explore how Design, Business and Engineering are currently working together on AI related problems and what insights have been gained so far, while outlining what the most important aspects are to explore for this design driven research.
Year(s) Of Engagement Activity 2019