Non-linear Spectral Contrast Stretching for In-car Speech Recognition
| Type of publication: | Idiap-RR |
| Citation: | li:rr07-53 |
| Number: | Idiap-RR-53-2007 |
| Year: | 2007 |
| Institution: | IDIAP |
| 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 | |
| Crossref by |
li:Interspeech:2007 |
| Added by: | [UNK] |
| Total mark: | 0 |
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