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 [BibTeX] [Marc21]
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 Li, Weifeng
Bourlard, Hervé
Crossref by li:Interspeech:2007
Added by: [UNK]
Total mark: 0
Attachments
  • li-idiap-rr-07-53.pdf
  • li-idiap-rr-07-53.ps.gz
Notes