Experiments on Adaptation Methods to Improve Acoustic Modeling for French Speech Recognition

Saeideh Mirzaei, Pierrick Milhorat, Jérôme Boudy, Gérard Chollet, Mikko Kurimo

Abstract

To improve the performance of Automatic Speech Recognition (ASR) systems, the models must be retrained in order to better adjust to the speaker’s voice characteristics, the environmental and channel conditions or the context of the task. In this project we focus on the mismatch between the acoustic features used to train the model and the vocal characteristics of the front-end user of the system. To overcome this mismatch, speaker adaptation techniques have been used. A significant performance improvement has been shown using using constrained Maximum Likelihood Linear Regression (cMLLR) model adaptation methods, while a fast adaptation is guaranteed by using linear Vocal Tract Length Normalization (lVTLN).We have achieved a relative gain of approximately 9.44% in the word error rate with unsupervised cMLLR adaptation. We also compare our ASR system with the Google ASR and show that, using adaptation methods, we exceed its performance.

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Paper Citation


in Harvard Style

Mirzaei S., Milhorat P., Boudy J., Chollet G. and Kurimo M. (2016). Experiments on Adaptation Methods to Improve Acoustic Modeling for French Speech Recognition . In Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-173-1, pages 278-282. DOI: 10.5220/0005703702780282


in Bibtex Style

@conference{icpram16,
author={Saeideh Mirzaei and Pierrick Milhorat and Jérôme Boudy and Gérard Chollet and Mikko Kurimo},
title={Experiments on Adaptation Methods to Improve Acoustic Modeling for French Speech Recognition},
booktitle={Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2016},
pages={278-282},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005703702780282},
isbn={978-989-758-173-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Experiments on Adaptation Methods to Improve Acoustic Modeling for French Speech Recognition
SN - 978-989-758-173-1
AU - Mirzaei S.
AU - Milhorat P.
AU - Boudy J.
AU - Chollet G.
AU - Kurimo M.
PY - 2016
SP - 278
EP - 282
DO - 10.5220/0005703702780282