Speaker identification for forensic applications

Phythian, Mark (1998) Speaker identification for forensic applications. Masters by Research thesis, Queensland University of Technology.

Abstract

A major application of Speaker Identification (SI) is suspect identification by voice. This thesis investigates techniques that can be used to improve SI technology as applied to suspect identification. Speech Coding techniques have become integrated into many of our modern voice communications systems. This prompts the question - how are automatic speaker identification systems and modern forensic identification techniques affected by the introduction of digitally coded speech channels? Presented in this thesis are three separate studies investigating the effects of speech coding and compression on current speaker recognition techniques. A relatively new Spectral Analysis technique - Higher Order Spectral Analysis (HOSA) - has been identified as a potential candidate for improving some aspects of forensic speaker identification tasks. Presented in this thesis is a study investigating the application of HOSA to improve the robustness of current ASR techniques in the presence of additive Gaussian noise. Results from our investigations reveal that incremental improvements in each of these aspects related to automatic and forensic identification are achievable.

Impact and interest:

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ID Code: 36079
Item Type: QUT Thesis (Masters by Research)
Additional Information: Presented to the School of Electrical and Electronic Systems Engineering, Queensland University of Technology.
Keywords: Speech processing systems, Automatic speech recognition, Voiceprints, Natural language processing (Computer science), signal processing, speech processing, speaker identification, speaker verification, speaker recognition, gaussian mixture model, speech coding, speech compression, higher order spectra, thesis, masters
Institution: Queensland University of Technology
Copyright Owner: Copyright Mark Phythian
Deposited On: 22 Sep 2010 13:04
Last Modified: 28 Jun 2017 14:42

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