Title
Robust Speech Recognition Features Based On Temporal Trajectory Filtering Of Frequency Band Spectrum
Abstract
This paper presents the use of a variety of filters in the temporal trajectories of frequency band spectrum to extract speech recognition features for environmental robustness. Three kind of filters for emphasizing the statistically important parts of speech are proposed. First, a bank of RASTA-like band-pass filters to fit the statistical peaks of modulation frequency band spectrum of speech are used. Secondly, a three-channel octave band-filter band with a smoothed rectangular window spline is applied. Thirdly, a data-driven filter is developed. Experimental results show that significant improvements for speech recognition using the proposed feature extraction approach under noisy environments can be achieved.
Year
DOI
Venue
1996
10.1109/ICSLP.1996.607742
ICSLP 96 - FOURTH INTERNATIONAL CONFERENCE ON SPOKEN LANGUAGE PROCESSING, PROCEEDINGS, VOLS 1-4
Keywords
Field
DocType
filtering,robustness,feature extraction,frequency modulation,spectrum,speech recognition,band pass filters
Speech enhancement,Octave,Pattern recognition,Band-pass filter,Frequency band,Computer science,Filter (signal processing),Speech recognition,Feature extraction,Robustness (computer science),Artificial intelligence,Frequency modulation
Conference
Citations 
PageRank 
References 
13
0.77
3
Authors
3
Name
Order
Citations
PageRank
Jia-Lin Shen116219.52
Wen-Liang Hwang2326.93
Lin-shan Lee31525182.03