Lip Location Normalized Training for Visual Speech Recognition
Summary :
This paper describes a method to normalize the lip position for improving the performance of a visual-information-based speech recognition system. Basically, there are two types of information useful in speech recognition processes; the first one is the speech signal itself and the second one is the visual information from the lips in motion. This paper tries to solve some problems caused by using images from the lips in motion such as the effect produced by the variation of the lip location. The proposed lip location normalization method is based on a search algorithm of the lip position in which the location normalization is integrated into the model training. Experiments of speaker-independent isolated word recognition were carried out on the Tulips1 and M2VTS databases. Experiments showed a recognition rate of 74.5% and an error reduction rate of 35.7% for the ten digits word recognition M2VTS database.
- Publication
- IEICE TRANSACTIONS on Information Vol.E83-D No.11 pp.1969-1977
- Publication Date
- 2000/11/25
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- PAPER
- Category
- Speech and Hearing
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Oscar VANEGAS, Keiichi TOKUDA, Tadashi KITAMURA, "Lip Location Normalized Training for Visual Speech Recognition" in IEICE TRANSACTIONS on Information,
vol. E83-D, no. 11, pp. 1969-1977, November 2000, doi: .
Abstract: This paper describes a method to normalize the lip position for improving the performance of a visual-information-based speech recognition system. Basically, there are two types of information useful in speech recognition processes; the first one is the speech signal itself and the second one is the visual information from the lips in motion. This paper tries to solve some problems caused by using images from the lips in motion such as the effect produced by the variation of the lip location. The proposed lip location normalization method is based on a search algorithm of the lip position in which the location normalization is integrated into the model training. Experiments of speaker-independent isolated word recognition were carried out on the Tulips1 and M2VTS databases. Experiments showed a recognition rate of 74.5% and an error reduction rate of 35.7% for the ten digits word recognition M2VTS database.
URL: https://global.ieice.org/en_transactions/information/10.1587/e83-d_11_1969/_p
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@ARTICLE{e83-d_11_1969,
author={Oscar VANEGAS, Keiichi TOKUDA, Tadashi KITAMURA, },
journal={IEICE TRANSACTIONS on Information},
title={Lip Location Normalized Training for Visual Speech Recognition},
year={2000},
volume={E83-D},
number={11},
pages={1969-1977},
abstract={This paper describes a method to normalize the lip position for improving the performance of a visual-information-based speech recognition system. Basically, there are two types of information useful in speech recognition processes; the first one is the speech signal itself and the second one is the visual information from the lips in motion. This paper tries to solve some problems caused by using images from the lips in motion such as the effect produced by the variation of the lip location. The proposed lip location normalization method is based on a search algorithm of the lip position in which the location normalization is integrated into the model training. Experiments of speaker-independent isolated word recognition were carried out on the Tulips1 and M2VTS databases. Experiments showed a recognition rate of 74.5% and an error reduction rate of 35.7% for the ten digits word recognition M2VTS database.},
keywords={},
doi={},
ISSN={},
month={November},}
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TY - JOUR
TI - Lip Location Normalized Training for Visual Speech Recognition
T2 - IEICE TRANSACTIONS on Information
SP - 1969
EP - 1977
AU - Oscar VANEGAS
AU - Keiichi TOKUDA
AU - Tadashi KITAMURA
PY - 2000
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E83-D
IS - 11
JA - IEICE TRANSACTIONS on Information
Y1 - November 2000
AB - This paper describes a method to normalize the lip position for improving the performance of a visual-information-based speech recognition system. Basically, there are two types of information useful in speech recognition processes; the first one is the speech signal itself and the second one is the visual information from the lips in motion. This paper tries to solve some problems caused by using images from the lips in motion such as the effect produced by the variation of the lip location. The proposed lip location normalization method is based on a search algorithm of the lip position in which the location normalization is integrated into the model training. Experiments of speaker-independent isolated word recognition were carried out on the Tulips1 and M2VTS databases. Experiments showed a recognition rate of 74.5% and an error reduction rate of 35.7% for the ten digits word recognition M2VTS database.
ER -
English
