DocumentCode
280971
Title
Parallel algorithms for automatic speech recognition
Author
Arriola, Y. ; Carrasco, R.A.
Author_Institution
Dept. of Electr. & Electron. Eng., Staffordshire Polytech., UK
fYear
1990
fDate
33224
Firstpage
42552
Lastpage
42557
Abstract
In the research, neural nets, or to be more precise, multilayer perceptrons (MLP), are used for the nonlinear phonetic mapping of the acoustic features. These phonetic outputs are used, subsequently, for the final probabilistic computation of the hidden Markov models (HMM). The speech recognition system was implemented and tested on real speech, low-pass filtered with a cut-off frequency of 3.8 kHz, and sampled at 8 kHz
Keywords
Markov processes; neural nets; parallel algorithms; speech recognition; 3.8 kHz; 8 kHz; acoustic features; automatic speech recognition; cut-off frequency; hidden Markov models; multilayer perceptrons; neural nets; nonlinear phonetic mapping; phonetic outputs; probabilistic computation; sampling;
fLanguage
English
Publisher
iet
Conference_Titel
Techniques for Speech Processing, IEE Colloquium on
Conference_Location
London
Type
conf
Filename
191457
Link To Document