DocumentCode
2260041
Title
An adaptive-beam pruning technique for continuous speech recognition
Author
Hamme, Hugo Van ; Aelten, Filip Van
Author_Institution
Lernout & Hauspie Speech Products NV, Wemmel, Belgium
Volume
4
fYear
1996
fDate
3-6 Oct 1996
Firstpage
2083
Abstract
Pruning is an essential paradigm to build HMM based large vocabulary speech recognisers that use reasonable computing resources. Unlikely sentence, word or subword hypotheses are removed from the search space when their likelihood falls outside a beam relative to the best scoring hypothesis. A method for automatically steering this beam such that the search space attains a predefined size is presented
Keywords
adaptive systems; hidden Markov models; search problems; speech processing; speech recognition; HMM based large vocabulary speech recognisers; adaptive beam pruning technique; computing resources; continuous speech recognition; likelihood; predefined size; scoring hypothesis; search space; subword hypotheses; Acoustic beams; Automatic control; Automatic speech recognition; Data mining; Decoding; Hidden Markov models; Histograms; Size control; Speech recognition; Vocabulary;
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.1996.607212
Filename
607212
Link To Document