Practical considerations for real-time implementation of speech-based gender detection

Authors:
Erik Scheme;Eduardo Castillo-Guerra;Kevin Englehart;Arvind Kizhanatham
Affiliations:
Institute of Bimedical Engineering, University of New Brunswick, Fredericton, NB, Canada;Dept. of Electrical and Computer Engineering, University of New Brunswick, Fredericton, NB, Canada;Institute of Bimedical Engineering, University of New Brunswick, Fredericton, NB, Canada;Diaphonics Inc., Halifax, Nova Scotia, Canada
Venue:
CIARP'06 Proceedings of the 11th Iberoamerican conference on Progress in Pattern Recognition, Image Analysis and Applications
Year:
2006

Citing 2
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Abstract

This paper describes a detailed analysis and implementation of a robust gender detector for audio stream applications. The implementation, based on melcepstral features and a Gaussian mixture model classifier, is designed to maximize gender classification performance in continuous speech. The described detector outperforms other reported systems based on statistically significant numbers of gender verifications (2136 unique speakers) obtained from the FISHER speech corpus. The system yields high accuracies for long and short utterances while a confidence figure of merit score for the decision ensures reliability in continuous audio streams.