Teager energy based feature parameters for speech recognition in car noise
Date
1999-10Source Title
IEEE Signal Processing Letters
Print ISSN
1070-9908
Publisher
Institute of Electrical and Electronics Engineers
Volume
6
Issue
10
Pages
259 - 261
Language
English
Type
ArticleItem Usage Stats
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Abstract
In this letter, a new set of speech feature parameters based on multirate signal processing and the Teager energy operator is introduced. The speech signal is first divided into nonuniform subbands in mel-scale using a multirate filterbank, then the Teager energies of the subsignals are estimated. Finally, the feature vector is constructed by log-compression and inverse discrete cosine transform (DCT) computation. The new feature parameters have robust speech recognition performance in the presence of car engine noise.
Keywords
Acoustic noiseCosine transforms
Digital filters
Feature extraction
Speech analysis
Vectors
Discrete cosine transform (DCT)
Multirate signal processing
Teager energy operator
Speech recognition