Teager energy based feature parameters for speech recognition in car noise
Date
1999-10
Authors
Editor(s)
Advisor
Supervisor
Co-Advisor
Co-Supervisor
Instructor
Source Title
IEEE Signal Processing Letters
Print ISSN
1070-9908
Electronic ISSN
Publisher
Institute of Electrical and Electronics Engineers
Volume
6
Issue
10
Pages
259 - 261
Language
English
Type
Journal Title
Journal ISSN
Volume Title
Series
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.