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Open AccessArticle

Forensic Speaker Verification Using Ordinary Least Squares

1
Campus of Ilha Solteira, São Paulo State University (UNESP), São Paulo 15385-000, Brazil
2
Telecommunications and Aeronautical Engineering, São Paulo State University (UNESP), São João da Boa, Vista SP 13876-750, Brazil
3
Automation and Control Engineering, Mato Grosso Federal Institute of Technology, Cuiabá 78005-200, Brazil
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(20), 4385; https://doi.org/10.3390/s19204385
Received: 30 August 2019 / Revised: 1 October 2019 / Accepted: 9 October 2019 / Published: 10 October 2019
In Brazil, the recognition of speakers for forensic purposes still relies on a subjectivity-based decision-making process through a results analysis of untrustworthy techniques. Owing to the lack of a voice database, speaker verification is currently applied to samples specifically collected for confrontation. However, speaker comparative analysis via contested discourse requires the collection of an excessive amount of voice samples for a series of individuals. Further, the recognition system must inform who is the most compatible with the contested voice from pre-selected individuals. Accordingly, this paper proposes using a combination of linear predictive coding (LPC) and ordinary least squares (OLS) as a speaker verification tool for forensic analysis. The proposed recognition technique establishes confidence and similarity upon which to base forensic reports, indicating verification of the speaker of the contested discourse. Therefore, in this paper, an accurate, quick, alternative method to help verify the speaker is contributed. After running seven different tests, this study preliminarily achieved a hit rate of 100% considering a limited dataset (Brazilian Portuguese). Furthermore, the developed method extracts a larger number of formants, which are indispensable for statistical comparisons via OLS. The proposed framework is robust at certain levels of noise, for sentences with the suppression of word changes, and with different quality or even meaningful audio time differences.
Keywords: forensic speaker comparison; forensic phonetics; voice processing; ordinary least squares (OLS); linear predictive coding (LPC) forensic speaker comparison; forensic phonetics; voice processing; ordinary least squares (OLS); linear predictive coding (LPC)
MDPI and ACS Style

Machado, T.J.; Vieira Filho, J.; de Oliveira, M.A. Forensic Speaker Verification Using Ordinary Least Squares. Sensors 2019, 19, 4385.

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