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Acoustic and facial features for speaker recognition / Matthew, Roach

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

Swansea University Author: Matthew, Roach

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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
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URI: https://cronfa.swan.ac.uk/Record/cronfa39141
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first_indexed 2018-03-22T05:12:37Z
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spelling 2018-03-21T20:19:50.9233657 v2 39141 2018-03-21 Acoustic and facial features for speaker recognition 9722c301d5bbdc96e967cdc629290fec 0000-0002-1486-5537 Matthew Roach Matthew Roach true false 2018-03-21 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 Other Proceedings 15th International Conference on Pattern Recognition. ICPR-2000 0 0 0 0001-01-01 10.1109/ICPR.2000.903534 COLLEGE NANME COLLEGE CODE Swansea University 2018-03-21T20:19:50.9233657 2018-03-21T20:19:50.6269491 College of Science Computer Science Roach M.J. 1 Brand J.D. 2 Mason J.S.D. 3 Matthew Roach 0000-0002-1486-5537 4
title Acoustic and facial features for speaker recognition
spellingShingle Acoustic and facial features for speaker recognition
Matthew, Roach
title_short Acoustic and facial features for speaker recognition
title_full Acoustic and facial features for speaker recognition
title_fullStr Acoustic and facial features for speaker recognition
title_full_unstemmed Acoustic and facial features for speaker recognition
title_sort Acoustic and facial features for speaker recognition
author_id_str_mv 9722c301d5bbdc96e967cdc629290fec
author_id_fullname_str_mv 9722c301d5bbdc96e967cdc629290fec_***_Matthew, Roach
author Matthew, Roach
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container_title Proceedings 15th International Conference on Pattern Recognition. ICPR-2000
institution Swansea University
doi_str_mv 10.1109/ICPR.2000.903534
college_str College of Science
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hierarchy_parent_title College of Science
department_str Computer Science{{{_:::_}}}College of Science{{{_:::_}}}Computer Science
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description 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
published_date 0001-01-01T19:13:33Z
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score 10.879041