CONF tsamuel:mlmi:2008/IDIAP Hilbert Envelope Based Features for Far-Field Speech Recognition Thomas, Samuel Ganapathy, Sriram Hermansky, Hynek EXTERNAL https://publications.idiap.ch/attachments/papers/2008/tsamuel-mlmi-2008.pdf PUBLIC https://publications.idiap.ch/index.php/publications/showcite/tsamuel:rr08-42 Related documents MLMI 2008 2008 IDIAP-RR 08-42 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). REPORT tsamuel:rr08-42/IDIAP Hilbert Envelope Based Features for Far-Field Speech Recognition Thomas, Samuel Ganapathy, Sriram Hermansky, Hynek EXTERNAL https://publications.idiap.ch/attachments/reports/2008/tsamuel-idiap-rr-08-42.pdf PUBLIC Idiap-RR-42-2008 2008 IDIAP To appear in MLMI 2008 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).