DocumentCode
2996586
Title
A neutral network for isolated-word recognition
Author
Gold, G.
Author_Institution
Lincoln Lab., MIT, Lexington, MA
fYear
1988
fDate
11-14 Apr 1988
Firstpage
44
Abstract
Algorithms that are implementable by artificial neural networks show promise of augmenting the field of automatic speech recognition. A specific approach to the problem of isolated-word recognition was initiated by Tank and Hopfield. These ideas were applied to a concatenated systems consisting of a vector quantizer, a time concentrator with vector sequences as input and allophones as output and a final stage with allophone sequence as input and isolated words as output. Improvements in the system are discussed; included are the addition of data-dependent `phenomenological´ rules that yield improved results for a single-speaker 35-word vocabulary isolated-word recognition task
Keywords
neural nets; speech recognition; allophones; artificial neural networks; automatic speech recognition; concatenated systems; data-dependent phonological rules; isolated-word recognition; phoneme; time concentrator; vector quantiser; vector sequences; Circuits; Delay; Error analysis; Filters; Gold; Hidden Markov models; Histograms; Speech; Testing; Vocabulary;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech, and Signal Processing, 1988. ICASSP-88., 1988 International Conference on
Conference_Location
New York, NY
ISSN
1520-6149
Type
conf
DOI
10.1109/ICASSP.1988.196505
Filename
196505
Link To Document