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Acoustic and facial features for speaker recognition

Matt Roach Orcid Logo, J.D. Brand, J.S.D. Mason

Proceedings 15th International Conference on Pattern Recognition. ICPR-2000

Swansea University Author: Matt Roach Orcid Logo

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DOI (Published version): 10.1109/icpr.2000.903534

Abstract

This paper gives an insight into biometrics used for speaker recognition. Three different biometrics are presented, based on: acoustic, geometric lip, and holistic facial features. Experiments are carried out using a corpus of the DAVID audio-visual database. Recognition accuracy is found to be simi...

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Published in: Proceedings 15th International Conference on Pattern Recognition. ICPR-2000
Published: IEEE Comput. Soc 2002
Online Access: http://dx.doi.org/10.1109/icpr.2000.903534
URI: https://cronfa.swan.ac.uk/Record/cronfa39141
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Abstract: This paper gives an insight into biometrics used for speaker recognition. Three different biometrics are presented, based on: acoustic, geometric lip, and holistic facial features. Experiments are carried out using a corpus of the DAVID audio-visual database. Recognition accuracy is found to be similar in the 2 domains. The geometric visual feature is based on a method of signature coding of the contour of the lips and the holistic feature is based on a mean dynamic signature, a method of capturing the motions of the face during a spoken utterance. Physical biometrics (static measurements) demand only small model sizes, perhaps just a single template, and therefore require less training data. Conversely behavioral biometrics contain more variation and demand more training data
College: Faculty of Science and Engineering

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