Non-linear Spectral Contrast Stretching for In-car Speech Recognition
Type of publication: | Conference paper |
Citation: | li:Interspeech:2007 |
Booktitle: | Interspeech-Eurospeech # to appear in html |
Year: | 2007 |
Note: | IDIAP-RR 07-53 |
Crossref: | li:rr07-53: |
Abstract: | In this paper, we present a novel feature normalization method in the log-scaled spectral domain for improving the noise robustness of speech recognition front-ends. In the proposed scheme, a non-linear contrast stretching is added to the outputs of log mel-filterbanks (MFB) to imitate the adaptation of the auditory system under adverse conditions. This is followed by a two-dimensional filter to smooth out the processing artifacts. The proposed MFCC front-ends perform remarkably well on CENSREC-2 in-car database with an average relative improvement of 29.3\% compared to baseline MFCC system. It is also confirmed that the proposed processing in log MFB domain can be integrated with conventional cepstral post-processing techniques to yield further improvements. The proposed algorithm is simple and requires only a small extra computation load. |
Userfields: | ipdmembership={speech}, |
Keywords: | |
Projects |
Idiap |
Authors | |
Added by: | [UNK] |
Total mark: | 0 |
Attachments
|
|
Notes
|
|
|