DocumentCode
312352
Title
POST: parallel object-oriented speech toolkit
Author
Hennebert, Jean ; Delacrétaz, Dijana Petrovska
Author_Institution
Circuits & Syst. Group, Swiss Federal Inst. of Technol., Lausanne, Switzerland
Volume
3
fYear
1996
fDate
3-6 Oct 1996
Firstpage
1966
Abstract
The authors give a short overview of POST, a parallel speech toolkit that is distributed freeware to academic institutions. The underlying idea of POST is that large computational problems, like the ones involved in automatic speech recognition (ASR), can be solved more cost effectively by using the aggregate power and memory of many computers. In its current version (January 96) and amongst other things, POST can perform simple feature extraction, training and testing of word and subword hidden Markov models (HMMs) with discrete and multi-Gaussian statistical modelling. The implementation of the parallelism is discussed and an evaluation of the performance on a telephone database is presented. A short introduction to Parallel Virtual Machine (PVM), the library through which the parallelism is achieved, is also given
Keywords
feature extraction; hidden Markov models; object-oriented programming; parallel processing; public domain software; software libraries; speech recognition; statistical analysis; telecommunication computing; telephony; POST; PVM library; academic institution; automatic speech recognition; discrete statistical modelling; feature extraction; freeware; large computational problems; multi-Gaussian statistical modelling; parallel object-oriented speech toolkit; performance evaluation; subword hidden Markov models; telephone database; testing; training; word hidden Markov models; Aggregates; Automatic speech recognition; Costs; Feature extraction; Hidden Markov models; Object oriented modeling; Parallel processing; Performance evaluation; Telephony; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Spoken Language, 1996. ICSLP 96. Proceedings., Fourth International Conference on
Conference_Location
Philadelphia, PA
Print_ISBN
0-7803-3555-4
Type
conf
DOI
10.1109/ICSLP.1996.608021
Filename
608021
Link To Document