Clap Your Hands! Calibrating Spectral Subtraction for Dereverberation
- Reverberation effects as observed by room microphones severely degrade the performance of automatic speech recognition systems. We investigate the use of dereverberation by spectral subtraction as proposed by Lebart and Boucher and introduce a simple approach to estimate the required decay parameter by clapping hands. Experiments on small vocabulary continuous speech recognition task on read speech show that using the calibrated dereverberation improves WER from 73.2 to 54.7 for the best microphone. In combination with system adaptation, the WER could be reduced to 28.2, which is only a 16% relative loss of performance comparison to using a headset instead of a room microphone.
| Author: | Uwe Zäh, Korbinian Riedhammer, Tobias Bocklet, Elmar Nöth |
|---|---|
| Parent Title (English): | 2010 IEEE International Conference on Acoustics, Speech and Signal Processing(ICASSP), Dallas, TX, USA, March 2010. |
| Document Type: | Conference Proceeding |
| Language: | English |
| Publication Year: | 2010 |
| Tag: | Speech Recognition; robustness |
| First Page: | 4226 |
| Last Page: | 4229 |
| faculties / departments: | Fakultät für Informatik |
| Dewey Decimal Classification: | 0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 000 Informatik, Informationswissenschaft, allgemeine Werke |
