Spoken word recognition using vocal tract shapes

Author

Kinugasa, H. ; Kamata, H. ; Ishida, Y.

Author_Institution

Dept. of Electron. & Commun., Meiji Univ., Kawasaki, Japan

Volume

1

fYear

1993

fDate

19-21 May 1993

Firstpage

133

Abstract

The estimation method of vocal tract shapes using an adaptive inverse filter for the discrete time signal has been proposed by T. Nakajima et al. (1978). In the present work, the authors use the adaptive inverse filter to autocorrelation coefficients to reduce the computation time. The estimated vocal tract shapes are used for the recognition experiment as input parameters. Speaker-independent word recognition results demonstrate the effectiveness of the method. In the experiment, dynamic programming matching is used. Experimental results show that the recognition rate using vocal tract shapes is higher than when using LPC (linear predictive coding) spectra

Keywords

adaptive filters; computational complexity; correlation methods; dynamic programming; inverse problems; parameter estimation; shape measurement; speech recognition; adaptive inverse filter; autocorrelation coefficients; computation time; dynamic programming matching; effectiveness; recognition rate; spoken word recognition; vocal tract shapes; Adaptive filters; Autocorrelation; Dynamic programming; Linear predictive coding; Production systems; Reflection; Resonance; Shape; Speech recognition; Speech synthesis;

fLanguage

English

Publisher

ieee

Conference_Titel

Communications, Computers and Signal Processing, 1993., IEEE Pacific Rim Conference on

Conference_Location

Victoria, BC

Print_ISBN

0-7803-0971-5

Type

conf

DOI

10.1109/PACRIM.1993.407204

Filename

407204