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The aim of the research work presented is to show a system that facilitates speech training for hearing impaired people. The system engineered combines both visual and acoustic speech data acquisition and analysis modules. The Active Shape Model method is used for extracting visual speech features from the shape and movement of the lips. The acoustic features extraction involves mel-cepstral analysis. Artificial Neural Networks are utilized as the classifier, feature vectors extracted combine both modalities of the human speech. Additional experiments with the degraded acoustic and/or visual information are carried out in order to test the system robustness against various distortions affecting the signals.
Author (s): Dalka, Piotr;
Kostek, Bozena;
Affiliation:
Gdansk University of Technology
(See document for exact affiliation information.)
AES Convention: 118
Paper Number:6462
Publication Date:
2005-05-06
Session subject:
Psychoacoustics, Perception, Listening Tests
DOI:
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Dalka, Piotr; Kostek, Bozena; 2005; Combining Visual and Acoustic Modalities to Ease Speech Recognition by Hearing Impaired People [PDF]; Gdansk University of Technology; Paper 6462; Available from: https://aes.org/publications/elibrary-page/?id=13178
Dalka, Piotr; Kostek, Bozena; Combining Visual and Acoustic Modalities to Ease Speech Recognition by Hearing Impaired People [PDF]; Gdansk University of Technology; Paper 6462; 2005 Available: https://aes.org/publications/elibrary-page/?id=13178
@inproceedings{Dalka2005combining,
title={{Combining Visual and Acoustic Modalities to Ease Speech Recognition by Hearing Impaired People}},
author={Dalka, Piotr and Kostek, Bozena},
year={2005},
month={may},
booktitle={Journal of the Audio Engineering Society},
publisher={Paper 6462; AES Convention 118; May 2005},
number={6462},
organization={AES},
}
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