Model-based dereverberation in the logmelspec domain for robust distant-talking speech recognition

Sehr A, Maas R, Kellermann W (2010)


Publication Language: English

Publication Status: Published

Publication Type: Conference contribution, Conference Contribution

Publication year: 2010

Pages Range: 4298-4301

Article Number: 5495671

Event location: Dallas, TX US

ISBN: 978-1-4244-4295-9

DOI: 10.1109/ICASSP.2010.5495671

Abstract

The REMOS (REverberation MOdeling for Speech recognition) concept for reverberation-robust distant-talking speech recognition, introduced in [1] for melspectral features, is extended in this contribution to logarithmic melspectral (logmelspec) features. Based on a combined acoustic model consisting of a hidden Markov model network and a reverberation model, REMOS determines clean-speech and reverberation estimates during recognition by an inner optimization operation. A reformulation of this inner optimization problem for logmelspec features, allowing an efficient solution by nonlinear optimization algorithms, is derived in this paper so that an efficient implementation of REMOS for logmelspec features becomes possible. Connected digit recognition experiments show that the proposed REMOS implementation significantly outperforms reverberantly-trained HMMs in highly reverberant environments. ©2010 IEEE.

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How to cite

APA:

Sehr, A., Maas, R., & Kellermann, W. (2010). Model-based dereverberation in the logmelspec domain for robust distant-talking speech recognition. In Proceedings of the 2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 (pp. 4298-4301). Dallas, TX, US.

MLA:

Sehr, Armin, Roland Maas, and Walter Kellermann. "Model-based dereverberation in the logmelspec domain for robust distant-talking speech recognition." Proceedings of the 2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010, Dallas, TX 2010. 4298-4301.

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