%Aigaion2 BibTeX export from Idiap Publications %Wednesday 11 December 2024 12:47:42 AM @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}, }