Teager energy based feature parameters for speech recognition in car noise

Date

1999-10

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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.

Source Title

IEEE Signal Processing Letters

Publisher

Institute of Electrical and Electronics Engineers

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Published Version (Please cite this version)

Language

English