DocumentCode :
290364
Title :
Large vocabulary continuous speech recognition of Wall Street Journal data
Author :
Aubert, X. ; Dugast, C. ; Ney, H. ; Steinbiss, V.
Author_Institution :
Philips GmbH Res. Lab. Aachen, Germany
Volume :
ii
fYear :
1994
fDate :
19-22 Apr 1994
Abstract :
We report on recent developments of the Philips large vocabulary speech recognition system and on our experiments with the Wall Street Journal (WSJ) corpus. A two-pass decoding has been devised that allows an easy integration of more complex language models. First, a word lattice is produced using a time synchronous beam search with a bigram language model. Next, a higher-order language model is applied to the lattice at the phrase level. The conditions insuring the validity of this approach are explained and practical results for trigram demonstrate its usefulness. The main system development stages on WSJ data are presented and our final recognizers are evaluated on Nov. ´92 and Nov. ´93 test-data for both 5 K and 20 K vocabularies
Keywords :
decoding; dictation; speech recognition; vocabulary; Philips dictation system; WSJ data; Wall Street Journal data; bigram language model; higher-order language model; language models; large vocabulary continuous speech recognition; time synchronous beam search; two-pass decoding; word lattice; Acoustic beams; Acoustic testing; Decoding; Hidden Markov models; Laboratories; Lattices; Speech recognition; System testing; Vectors; Vocabulary;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1994. ICASSP-94., 1994 IEEE International Conference on
Conference_Location :
Adelaide, SA
ISSN :
1520-6149
Print_ISBN :
0-7803-1775-0
Type :
conf
DOI :
10.1109/ICASSP.1994.389702
Filename :
389702
Link To Document :
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