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Proceedings Paper

Application of time-frequency analysis methods to speaker verification
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Paper Abstract

Time-Frequency Analysis has previously been successfully applied to characterize and quantify a variety of acoustic signals, including marine mammal sounds. In this research, Time-Frequency analysis is applied to human speech signals in an effort to reveal signal structure salient to the biometric speaker verification challenge. Prior approaches to speaker verification have relied upon signal processing analysis such as linear prediction or weighted Cepstrum spectral representations of segments of speech and classification techniques based on stochastic pattern matching. The authors believe that the classification of identity of a speaker based on time-frequency representation of short time events occurring in speech could have substantial advantages. Using these ideas, a speaker verification algorithm was developed1 and has been refined over the past several years. In this presentation, the authors describe the testing of the algorithm using a large speech database, the results obtained, and recommendations for further improvements.

Paper Details

Date Published: 25 August 2006
PDF: 12 pages
Proc. SPIE 6313, Advanced Signal Processing Algorithms, Architectures, and Implementations XVI, 63130P (25 August 2006); doi: 10.1117/12.681019
Show Author Affiliations
W. J. Williams, Quantum Signal LLC (United States)
R. W. Bossemeyer, Quantum Signal LLC (United States)

Published in SPIE Proceedings Vol. 6313:
Advanced Signal Processing Algorithms, Architectures, and Implementations XVI
Franklin T. Luk, Editor(s)

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