HMM continuous speech recognition using predictive LR parsing
- 13 January 2003
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- No. 15206149,p. 703-706
- https://doi.org/10.1109/icassp.1989.266524
Abstract
The authors propose a continuous-speech recognition method that uses an accurate and efficient parsing mechanism, an LR parser, and drives HMM (hidden Markov model) modules directly without any intervening structures such as a phoneme lattice. The method was tested in Japanese phrase recognition experiments. Two grammars were prepared, a general Japanese grammar and a task-specific grammar. The phrase recognition rate with the general grammar was 72% for top candidates and 95% for the five best candidates. With the task-specific grammar, recognition rate was 80% and 99% respectively.<>Keywords
This publication has 10 references indexed in Scilit:
- Improvement of word recognition results by trigram modelPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- BYBLOS: The BBN continuous speech recognition systemPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- An efficient word lattice parsing algorithm for continuous speech recognitionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- Spoken sentence recognition by time-synchronous parsing algorithm of context-free grammarPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- Dynamic programming speech recognition using a context-free grammarPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- Large-vocabulary speaker-independent continuous speech recognition using HMMPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Statistical language modeling using a small corpus from an application domainPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Efficient Parsing for Natural LanguagePublished by Springer Nature ,1986
- An efficient context-free parsing algorithmCommunications of the ACM, 1970
- Recognition and parsing of context-free languages in time n3Information and Control, 1967