DocumentCode :
3298976
Title :
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
Link To Document :
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