DocumentCode
3074359
Title
Connected digit recognition using vector quantization
Author
Bourlard, H. ; Wellekens, Chr J. ; Ney, Hermann
Author_Institution
Philips Research Laboratory, Brussels, Belgium
Volume
9
fYear
1984
fDate
30742
Firstpage
413
Lastpage
416
Abstract
The principles of classification applied to the representation of the words in a vocabulary lead to the clustering of the acoustic vectors into prototype vectors. For a small number of prototypes, recognition scores comparable to those observed with unclustered vocabularies are obtained with a highly reduced computation time. Two different forms (deterministic and stochastic) of the single-level recognition method for concatenated words are described and the improvements obtained by vector quantization are put into evidence. The use of prototypes in the training phase of the finite stochastic automata representing a vocabulary word is also described.
Keywords
Acoustic distortion; Character recognition; Distortion measurement; Dynamic programming; Laboratories; Prototypes; Speech recognition; Stochastic processes; Vector quantization; Vocabulary;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP '84.
Type
conf
DOI
10.1109/ICASSP.1984.1172585
Filename
1172585
Link To Document