| Presentation # | 10 |
| Session: | ASR II |
| Location: | Kallirhoe Hall |
| Session Time: | Thursday, December 20, 13:30 - 15:30 |
| Presentation Time: | Thursday, December 20, 13:30 - 15:30 |
| Presentation: |
Poster
|
| Topic: |
Speech recognition and synthesis: |
| Paper Title: |
MULTI-BAND PROCESSING WITH GABOR FILTERS AND TIME DELAY NEURAL NETS FOR NOISE ROBUST SPEECH RECOGNITION |
| Authors: |
György Kovács, MTA-SZTE Research Group on Artificial Intelligence, Hungary; László Tóth, University of Szeged, Hungary; Gábor Gosztolya, MTA-SZTE Research Group on Artificial Intelligence, Hungary |
| Abstract: |
Spectro-temporal feature extraction and multi-band processing were both invented with the goal of increasing the robustness of speech recognisers. However, although these methods have been in use for a long time now, and they are evidently compatible, few attempts have been made to combine them. This is why here we investigate the combination of multi-band processing with the use of spectro-temporal Gabor filters. First, based on the TIMIT corpus, we optimise their meta-parameters like the overlap, and the number of bands. Then we verify the cross-corpus viability of our multi-band processing approach on the Aurora-4 corpus. Lastly, we combine our method with the recently proposed channel dropout method. Our results show that this combination not only leads to lower error rates than those got using either multi-band processing or channel dropout, but these results compare favourably to those recently reported for the clean training scenario on the Aurora-4 corpus. |