Application of adaptive wavelets for speech coding

Author

Kadambe, Shubha ; Srinivasan, Pramila

Author_Institution

AT&T Bell Labs., Murray Hill, NJ, USA

fYear

1994

fDate

25-28 Oct 1994

Firstpage

632

Lastpage

635

Abstract

The paper describes a high quality, low bit rate (about 2.4 k bits per sec) speech coder which uses adaptive wavelets to model speech. The optimal wavelet parameters which correspond to the speech model that produced a particular sound are obtained using a feed forward neural network. These parameters are then quantized using scalar and vector quantization (VQ) techniques to reduce the number of bits required to transmit a speech signal. Both these quantizers are described in the paper. The bit rate i.e., the number of bits per second of speech for both the quantizers is computed and it is shown that the bit rate can be reduced significantly using a VQ method. The comparative perception results that are obtained by listening to the synthesized speech using both scaler and vector quantized wavelet parameters are reported. In addition, the change in error obtained by varying the number of wavelets to represent a speech signal is analyzed

Keywords

adaptive codes; channel capacity; error statistics; feedforward neural nets; hearing; optimisation; speech coding; vector quantisation; wavelet transforms; adaptive wavelets; bit rate; comparative perception results; error; feed forward neural network; optimal wavelet parameters; scalar quantization; sound; speech coder; speech coding; speech signal; vector quantization; Bit rate; Feedforward neural networks; Feeds; Neural networks; Signal synthesis; Speech analysis; Speech coding; Speech synthesis; Vector quantization; Wavelet analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Time-Frequency and Time-Scale Analysis, 1994., Proceedings of the IEEE-SP International Symposium on

Conference_Location

Philadelphia, PA

Print_ISBN

0-7803-2127-8

Type

conf

DOI

10.1109/TFSA.1994.467272

Filename

467272