%Aigaion2 BibTeX export from Idiap Publications
%Tuesday 27 February 2024 04:13:15 AM

@INPROCEEDINGS{tsamuel:interspeech-1:2008,
         author = {Ganapathy, Sriram and Thomas, Samuel and Hermansky, Hynek},
       projects = {Idiap},
          title = {Front-end for Far-field Speech Recognition based on Frequency Domain Linear Prediction},
      booktitle = {Interspeech 2008},
           year = {2008},
           note = {IDIAP-RR 08-17},
       crossref = {tsamuel:rr08-17},
       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.},
            pdf = {https://publications.idiap.ch/attachments/papers/2008/tsamuel-interspeech-1-2008.pdf},
     postscript = {ftp://ftp.idiap.ch/pub/papers/2008/tsamuel-interspeech-1-2008.ps.gz},
ipdmembership={speech},
}



crossreferenced publications: 
@TECHREPORT{tsamuel:rr08-17,
         author = {Ganapathy, Sriram and Thomas, Samuel and Hermansky, Hynek},
       projects = {Idiap},
          title = {Front-end for Far-field Speech Recognition based on Frequency Domain Linear Prediction},
           type = {Idiap-RR},
         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.},
            pdf = {https://publications.idiap.ch/attachments/reports/2008/tsamuel-idiap-rr-08-17.pdf},
     postscript = {ftp://ftp.idiap.ch/pub/reports/2008/tsamuel-idiap-rr-08-17.ps.gz},
ipdmembership={speech},
}