DocumentCode :
1854624
Title :
Lattice-based discriminative training for large vocabulary speech recognition
Author :
Valtchev, V. ; Odell, J.J. ; Woodland, P.C. ; Young, S.J.
Author_Institution :
Dept. of Eng., Cambridge Univ., UK
Volume :
2
fYear :
1996
fDate :
7-10 May 1996
Firstpage :
605
Abstract :
This paper describes a framework for optimising the parameters of a continuous density HMM-based large vocabulary recognition system using a maximum mutual information estimation (MMIE) criterion. To limit the computational complexity arising from the need to find confusable speech segments in the large search space of alternative utterance hypotheses, word lattices generated from the training data are used. Experiments are presented on the Wall Street journal database using up to 66 hours of training data. These show that lattices combined with an improved estimation algorithm makes MMIE training practicable even for very complex recognition systems and large training sets. Furthermore, experimental results show that MMIE training can yield useful increases in recognition accuracy
Keywords :
computational complexity; hidden Markov models; maximum likelihood estimation; speech recognition; MMIE training; Wall Street journal database; computational complexity; confusable speech segments; continuous density HMM; estimation algorithm; experimental results; large search space; large training sets; large vocabulary speech recognition; lattice-based discriminative training; maximum mutual information estimation; recognition accuracy; training data; utterance hypotheses; word lattices; Context modeling; Databases; Encoding; Hidden Markov models; Laboratories; Lattices; Maximum likelihood estimation; Speech recognition; Training data; Vocabulary;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1996. ICASSP-96. Conference Proceedings., 1996 IEEE International Conference on
Conference_Location :
Atlanta, GA
ISSN :
1520-6149
Print_ISBN :
0-7803-3192-3
Type :
conf
DOI :
10.1109/ICASSP.1996.543193
Filename :
543193
Link To Document :
بازگشت