%Aigaion2 BibTeX export from Idiap Publications
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@INPROCEEDINGS{tsamuel:mlmi:2008,
         author = {Thomas, Samuel and Ganapathy, Sriram and Hermansky, Hynek},
       projects = {Idiap},
          title = {Hilbert Envelope Based Features for Far-Field Speech Recognition},
      booktitle = {MLMI 2008},
           year = {2008},
           note = {IDIAP-RR 08-42},
       crossref = {tsamuel:rr08-42},
       abstract = {Automatic speech recognition (ASR) systems, trained on speech signals from close-talking microphones, generally fail in recognizing far-field speech. In this paper, we present a Hilbert Envelope based feature extraction technique to alleviate the artifacts introduced by room reverberations. The proposed technique is based on modeling temporal envelopes of the speech signal in narrow sub-bands using Frequency Domain Linear Prediction (FDLP). ASR experiments on far-field speech using the proposed FDLP features show significant performance improvements when compared to other robust feature extraction techniques (average relative improvement of $43 \%$ in word error rate).},
            pdf = {https://publications.idiap.ch/attachments/papers/2008/tsamuel-mlmi-2008.pdf},
     postscript = {ftp://ftp.idiap.ch/pub/papers/2008/tsamuel-mlmi-2008.ps.gz},
ipdmembership={speech},
}



crossreferenced publications: 
@TECHREPORT{tsamuel:rr08-42,
         author = {Thomas, Samuel and Ganapathy, Sriram and Hermansky, Hynek},
       projects = {Idiap},
          title = {Hilbert Envelope Based Features for Far-Field Speech Recognition},
           type = {Idiap-RR},
         number = {Idiap-RR-42-2008},
           year = {2008},
    institution = {IDIAP},
           note = {To appear in MLMI 2008},
       abstract = {Automatic speech recognition (ASR) systems, trained on speech signals from close-talking microphones, generally fail in recognizing far-field speech. In this paper, we present a Hilbert Envelope based feature extraction technique to alleviate the artifacts introduced by room reverberations. The proposed technique is based on modeling temporal envelopes of the speech signal in narrow sub-bands using Frequency Domain Linear Prediction (FDLP). ASR experiments on far-field speech using the proposed FDLP features show significant performance improvements when compared to other robust feature extraction techniques (average relative improvement of $43 \%$ in word error rate).},
            pdf = {https://publications.idiap.ch/attachments/reports/2008/tsamuel-idiap-rr-08-42.pdf},
     postscript = {ftp://ftp.idiap.ch/pub/reports/2008/tsamuel-idiap-rr-08-42.ps.gz},
ipdmembership={speech},
}