Voice and Identity: source, filter, biometric

The voice has fascinated philosophers, writers and scientists throughout history, especially as a marker of human identity. Formal analysis of voice is conducted in strikingly different frameworks, some developed largely in arts & humanities disciplines (linguistics and phonetics), and others in the sciences (engineering, physics, computer science). These frameworks differ in focus, assumptions, and in methods used to test their performance and reliability. Remarkably little work has sought to integrate them, resulting in only limited under-standing of their respective benefits and drawbacks, and of their degree of compatibility. This is of particular importance in the applied domain of forensic speech science, where the individual properties of the voice are treated as a biometric. Forensic voice (or speaker) comparison (FVC) is increasingly called for in courts worldwide. Typically, comparison is made between the voice of a suspect, and a voice recorded in criminal activity (e.g. via covert surveillance of drug deals or terrorist plots). The aim of FVC is to aid the court in assessing the likelihood that the speaker in the recordings is the same person, as opposed to a different person. There is a growing consensus that an integrated approach is needed for significant progress to be made towards a more reliable and robust procedure for FVC.

In this proposal we seek to assess the comparative performance of voice analysis based on linguistic-phonetic methods, and automatic (computational) systems. We will explore the performance of the methods on the same data to assess their relative strengths, the consistency of their results and error patterns, and thus the potential for phonetic and automatic methods to be integrated. The ultimate aim is to improve methods in FVC, taking a major step towards the development of a methodology that is more transparent, validated, and replicable. This outcome will benefit academics and forensic practitioners, the public, judicial systems, and investigative/security agencies. More generally, the project answers recent calls to improve the quality of forensic evidence of all kinds, making forensic sciences more transparent and more carefully regulated (e.g. Law Commission of England & Wales 2011).

The project addresses the AHRC's focus theme, Science in Culture: it (i) explores the capacity of linguistic-phonetic techniques for advancing scientific methods; (ii) explores how methods developed in both the sciences and arts might be integrated; (iii) improves understanding of the comparative roles of expertise from the sciences and humanities in FVC; and (iv) aims to improve public confidence in forensic evidence.

The outcomes of this research will also have a number of economic and societal beneficiaries:

1. Commercial private sector - forensic voice analysts

The findings of this project will have an immediate impact on the analytic procedures applied to forensic voice comparison cases. Beneficiaries will include both private and government laboratories. In the private sector, the benefits will be felt directly J P French Associates, as collaborators in the project. Dissemination to other national and international labs will take place at the wide range of conferences and specialist meetings outlined in the proposal. In particular, the project will improve expert analyses by identifying the global outputs from the source and filter which offer the greatest speaker-discriminatory power, which can then be applied in casework, as well as providing an understanding of the types of errors made by different approaches. The research will also benefit private companies developing ASR systems (incl. Agnitio, manufacturers of the leading commercially available ASR software, BATVOX), by offering different automatic-style variables for analysis and ultimately improving current error rates.

2. Government agencies

This research will provide the same benefits to both national and international government agencies as those outlined for the commercial private sector. In particular, the research will improve the forensic voice comparison analyses performed by governmental forensics laboratories. The applicants have close working relationships with many other agencies, including MI5, the Netherlands Forensic Institute, Bundeskriminalamt (German State Labs), the Royal Canadian Mounted Police, and the Estonian Forensic Science Institute.

3. Regulators/policy makers

This project will be of direct relevance to the UK Forensic Science Regulator (FSR), established in 2012 to regulate practice in forensic practice in disciplines in the UK. Co-PI French is the chair of the Forensic Speech and Audio committee of the FSR, ensuring the research can be disseminated to all registered practitioners, and, if appropriate, the implications for forensic practice can be enshrined in the regulations for expert witness policy and practice. As part of the dissemination of this research, we will also contribute towards the Home Office Biometrics Working Group. Therefore, the findings will contribute towards the advancement, improvement and standardisation (in particular the development of best practices) of forensic voice comparison evidence presented to UK courts.

4. Judicial system

As end-users of expert evidence, the findings of this project will necessarily have implications for the judicial system at large. The results are intended to improve the quality of forensic voice comparison evidence in courts, both by improving the results of forensic speech analysis and also leading to better understanding of the limitations of different methods. The research will also indirectly help to develop the level of understanding of speech evidence by the courts by increasing the degree of standardisation across experts and analyses.

5. Public

The general public benefit from the project, since justice is determined by the quality of forensic evidence presented to the courts. It is also hoped that the findings will increase public understanding of technical analysis as applied to forensic evidence, in particular to assist in understanding what is often regarded as opaque 'black-box' evidence such as that produced by ASR systems.