NDLI: A wavelet and filter bank framework for phonetic classification

Content Provider	IEEE Xplore Digital Library
Author	Choueiter, G.F. Glass, J.R.
Copyright Year	2005
Description	Author affiliation: Lab. for Comput. Sci. & Artificial Intelligence, MIT, Cambridge, MA, USA (Choueiter, G.F.; Glass, J.R.)
Abstract	We present a wavelet and filter bank framework for context-independent phonetic classification with the aim of extending the work towards a full speech recognition system. The framework addresses the limitations of the Fourier analysis stage commonly used for short-time spectral representation of speech signals. Also, previous research pertaining to wavelet analysis for speech processing mostly makes use of off-the-shelf wavelets and dyadic-based signal decomposition. Our framework provides more flexibility by taking advantage of the relationship between wavelet transforms and filter banks, and using two filter design techniques as well as 'rational' wavelets. On the standard 39 phone TIMIT classification task, we achieve 22.9% error rate on the core test set using rational filter banks and 4-fold aggregation. This is improved to 18.5% when combined with multiple classifiers defined over non-wavelet acoustic measurements.
Sponsorship	IEEE Signal Processing Soc
File Size	291927
File Format	PDF
ISBN	0780388747
ISSN	15206149
DOI	10.1109/ICASSP.2005.1415268
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-03-23
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Filter bank Wavelet analysis Wavelet transforms Signal analysis Speech analysis Signal resolution Band pass filters Frequency Channel bank filters Glass
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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