Front-end for Far-field Speech Recognition based on Frequency Domain Linear Prediction
| Type of publication: | Idiap-RR |
| Citation: | tsamuel:rr08-17 |
| Number: | Idiap-RR-17-2008 |
| Year: | 2008 |
| Institution: | IDIAP |
| Abstract: | Automatic Speech Recognition (ASR) systems usually fail when they encounter speech from far-field microphone in reverberant environments. This is due to the application of short-term feature extraction techniques which do not compensate for the artifacts introduced by long room impulse responses. In this paper, we propose a front-end, based on Frequency Domain Linear Prediction (FDLP,',','), that tries to remove reverberation artifacts present in far-field speech. Long temporal segments of far-field speech are analyzed in narrow frequency sub-bands to extract FDLP envelopes and residual signals. Filtering the residual signals with gain normalized inverse FDLP filters result in a set of sub-band signals which are synthesized to reconstruct the signal back. ASR experiments on far-field speech data processed by the proposed front-end show significant improvements (relative reduction of $30 \%$ in word error rate) compared to other robust feature extraction techniques. |
| Userfields: | ipdmembership={speech}, |
| Keywords: | |
| Projects |
Idiap |
| Authors | |
| Crossref by |
tsamuel:interspeech-1:2008 |
| Added by: | [UNK] |
| Total mark: | 0 |
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