Robust MVDR-based feature extraction for speech recognition

Authors:
Sanaz Seyedin;Seyed Mohammad Ahadi
Affiliations:
Electrical Engineering Department, Amirkabir University of Technology, Tehran, Iran;Electrical Engineering Department, Amirkabir University of Technology, Tehran, Iran
Venue:
ICICS'09 Proceedings of the 7th international conference on Information, communications and signal processing
Year:
2009

Citing 2
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Digital spectral analysis: with applications

Digital spectral analysis: with applications
Robust Feature Extraction for Continuous Speech Recognition Using the MVDR Spectrum Estimation Method

IEEE Transactions on Audio, Speech, and Language Processing

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Abstract

This paper presents a novel noise robust feature extraction method for speech recognition. It is based on making the Minimum Variance Distortionless Response (MVDR) power spectrum estimation method robust against noise. This robustness is obtained by modifying the distortionless constraint of the MVDR spectral estimation method via weighting the sub-band power spectrum values based on the sub-band signal to noise ratios. The above method, when evaluated on Aurora 2 task, outperformed both the MFCC features as the baseline and the MVDR-based features in different noisy conditions.