On the application of reverberation suppression to robust speech recognition

Conference contribution
(Conference Contribution)


Publication Details

Author(s): Maas R, Habets E, Sehr A, Kellermann W
Publication year: 2012
Pages range: 297-300
ISBN: 9781467300469
Language: English


Abstract


In this paper, we study the effect of the design parameters of a single-channel reverberation suppression algorithm on reverberation-robust speech recognition. At the same time, reverberation compensation at the speech recognizer is investigated. The analysis reveals that it is highly beneficial to attenuate only the reverberation tail after approximately 50 ms while coping with the early reflections and residual late-reverberation by training the recognizer on moderately reverberant data. It will be shown that the overall system at its optimum configuration yields a very promising recognition performance even in strongly reverberant environments. Since the reverberation suppression algorithm is evidenced to significantly reduce the dependency on the training data, it allows for a very efficient training of acoustic models that are suitable for a wide range of reverberation conditions. Finally, experiments with an "ideal" reverberation suppression algorithm are carried out to cross-check the inferred guidelines. © 2012 IEEE.


FAU Authors / FAU Editors

Habets, Emanuël Prof. Dr.
Professur für wahrnehmungsbasierte räumliche Audiosignalverarbeitung (AudioLabs) (Stiftungsprofessur)
Kellermann, Walter Prof. Dr.-Ing.
Professur für Nachrichtentechnik
Maas, Roland
Lehrstuhl für Multimediakommunikation und Signalverarbeitung
Sehr, Armin Dr.-Ing.
Professur für Nachrichtentechnik


How to cite

APA:
Maas, R., Habets, E., Sehr, A., & Kellermann, W. (2012). On the application of reverberation suppression to robust speech recognition. In Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) (pp. 297-300). Kyoto, JP.

MLA:
Maas, Roland, et al. "On the application of reverberation suppression to robust speech recognition." Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Kyoto 2012. 297-300.

BibTeX: 

Last updated on 2019-16-04 at 02:23