Classifying visemes for automatic lipreading

Michiel Visser; Mannes Poel; Antinus Nijholt

doi:10.1007/3-540-48239-3_65

Classifying visemes for automatic lipreading

Michiel Visser, Mannes Poel, Antinus Nijholt

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

12 Citations (Scopus)

Abstract

Automatic lipreading is automatic speech recognition that uses only visual information. The relevant data in a video signal is isolated and features are extracted from it. From a sequence of feature vectors, where every vector represents one video image, a sequence of higher level semantic elements is formed. These semantic elements are "visemes" the visual equivalent of "phonemes" The developed prototype uses a Time Delayed Neural Network to classify the visemes.

Original language	Undefined
Title of host publication	International Workshop Text, Speech and Dialogue (TSD'99)
Editors	Vaclav Matousek, Pavel Mautner, Jana Ocelikovi, Petr Sojka
Place of Publication	Berlin
Publisher	Springer
Pages	349-352
Number of pages	4
ISBN (Print)	3-540-66494-7
DOIs	https://doi.org/10.1007/3-540-48239-3_65
Publication status	Published - 1 Sept 1999
Event	2nd Text, Speech & Dialogue Workshop, TSD 1999 - Plzen, Czech Republic Duration: 13 Sept 1999 → 17 Sept 1999 Conference number: 2

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer Verlag
Volume	1692
ISSN (Print)	0302-9743

Workshop

Workshop	2nd Text, Speech & Dialogue Workshop, TSD 1999
Abbreviated title	TSD 1999
Country/Territory	Czech Republic
City	Plzen
Period	13/09/99 → 17/09/99

Keywords

EWI-9759
IR-64013
METIS-119592
HMI-MI: MULTIMODAL INTERACTIONS

Access to Document

10.1007/3-540-48239-3_65

http://eprints.eemcs.utwente.nl/secure2/9759/01/tsd1999.pdf

Cite this

@inproceedings{ffebb10e45cc47529eebf3059c5dde69,

title = "Classifying visemes for automatic lipreading",

abstract = "Automatic lipreading is automatic speech recognition that uses only visual information. The relevant data in a video signal is isolated and features are extracted from it. From a sequence of feature vectors, where every vector represents one video image, a sequence of higher level semantic elements is formed. These semantic elements are {"}visemes{"} the visual equivalent of {"}phonemes{"} The developed prototype uses a Time Delayed Neural Network to classify the visemes.",

keywords = "EWI-9759, IR-64013, METIS-119592, HMI-MI: MULTIMODAL INTERACTIONS",

author = "Michiel Visser and Mannes Poel and Antinus Nijholt",

year = "1999",

month = sep,

day = "1",

doi = "10.1007/3-540-48239-3_65",

language = "Undefined",

isbn = "3-540-66494-7",

series = "Lecture Notes in Computer Science",

publisher = "Springer",

pages = "349--352",

editor = "Vaclav Matousek and Pavel Mautner and Jana Ocelikovi and Petr Sojka",

booktitle = "International Workshop Text, Speech and Dialogue (TSD'99)",

note = "2nd Text, Speech & Dialogue Workshop, TSD 1999 ; Conference date: 13-09-1999 Through 17-09-1999",

}

Visser, M, Poel, M & Nijholt, A 1999, Classifying visemes for automatic lipreading. in V Matousek, P Mautner, J Ocelikovi & P Sojka (eds), International Workshop Text, Speech and Dialogue (TSD'99). Lecture Notes in Computer Science, vol. 1692, Springer, Berlin, pp. 349-352, 2nd Text, Speech & Dialogue Workshop, TSD 1999, Plzen, Czech Republic, 13/09/99. https://doi.org/10.1007/3-540-48239-3_65

Classifying visemes for automatic lipreading. / Visser, Michiel; Poel, Mannes ; Nijholt, Antinus.
International Workshop Text, Speech and Dialogue (TSD'99). ed. / Vaclav Matousek; Pavel Mautner; Jana Ocelikovi; Petr Sojka. Berlin: Springer, 1999. p. 349-352 (Lecture Notes in Computer Science; Vol. 1692).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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AU - Poel, Mannes

AU - Nijholt, Antinus

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N2 - Automatic lipreading is automatic speech recognition that uses only visual information. The relevant data in a video signal is isolated and features are extracted from it. From a sequence of feature vectors, where every vector represents one video image, a sequence of higher level semantic elements is formed. These semantic elements are "visemes" the visual equivalent of "phonemes" The developed prototype uses a Time Delayed Neural Network to classify the visemes.

AB - Automatic lipreading is automatic speech recognition that uses only visual information. The relevant data in a video signal is isolated and features are extracted from it. From a sequence of feature vectors, where every vector represents one video image, a sequence of higher level semantic elements is formed. These semantic elements are "visemes" the visual equivalent of "phonemes" The developed prototype uses a Time Delayed Neural Network to classify the visemes.

KW - EWI-9759

KW - IR-64013

KW - METIS-119592

KW - HMI-MI: MULTIMODAL INTERACTIONS

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