Introducing Temporal Asymmetries in Feature Extraction for Automatic Speech Recognition

We propose a new auditory inspired feature extraction technique for automatic speech recognition (ASR). Features are extracted by filtering the temporal trajectory of spectral energies in each critical band of speech by a bank of finite impulse response (FIR) filters. Impulse responses of these filters are derived from a modified Gabor envelope in order to emulate asymmetries of the temporal receptive field (TRF) profiles observed in higher level auditory neurons. We obtain $11.4\% $ relative improvement in word error rate on OGI-Digits database and, $3.2\%$ relative improvement in phoneme error rate on TIMIT database over the MRASTA technique.


Year:
2008
Publisher:
IDIAP
Laboratories:




 Record created 2010-02-11, last modified 2018-03-17

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