Adaptive wavelet based phoneme recognition

Author

Kadambe, Shubha ; Srinivasan, Pramila

Author_Institution

Atlantic Aerosp. Electron. Corp., Greenbelt, MD, USA

Volume

2

fYear

1997

fDate

3-6 Aug 1997

Firstpage

720

Abstract

The phoneme recognition systems are part of Automatic Speech Recognition (ASR) systems. These systems are used in telecommunication to provide automatic services such as “call collect”, “directory assistance”, etc. to the subscribers. The elimination of assistance of human operators saves operating costs for the telecommunication companies in millions of dollars. In this paper, a phoneme recognizer based on adaptive wavelets is described. The experimental results of this recognizer using TIMIT database is provided. This experimental results also include the comparative study with a Hidden Markov Model (HMM) based phoneme recognizer

Keywords

adaptive signal processing; neural nets; pattern classification; signal sampling; speech recognition; wavelet transforms; TIMIT database; adaptive wavelet based phoneme recognition; automatic speech recognition systems; automatic telecommunication services; phoneme recognizer; sampling scheme; Aerospace electronics; Automatic speech recognition; Continuous wavelet transforms; Hidden Markov models; Humans; Libraries; Neural networks; Neurons; Sampling methods; Shape;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 1997. Proceedings of the 40th Midwest Symposium on

Conference_Location

Sacramento, CA

Print_ISBN

0-7803-3694-1

Type

conf

DOI

10.1109/MWSCAS.1997.662176

Filename

662176