Presentation 1996/12/13
Continuous Speech Recognition Using LR Parsing With Effective Hypotheses Merging Mechanism
Tomokazu YAMADA, Shoichi MATSUNAGA, Shigeki SAGAYAMA,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) This paper describes a Viterbi search algorithm for continuous speech recognition using context-dependent phone models under the constraint defined by a context-free grammar (CFG). It is based on a frame synchronous LR parser which dynamically generates a finite state network (FSN) from the CFG with an efficient path merging mechanism. Full context-dependency (intra- and inter-word context) is taken into account. This paper first describes the algorithm and the processing mechanism, then compares the experimental results of our algorithm and the conventional tree-based HMM-LR speech recognition algorithm which uses HMMs and an LR parser in phone-synchronous processing. The experiments show that our algorithm runs faster than the HMM-LR algorithm with an equivalent recognition accuracy.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Speech Recognition / HMM / LR Parser / One-pass Search / Finite State Automaton
Paper # NLC96-54,SP96-85
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Committee NLC
Conference Date 1996/12/13(1days)
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Paper Information
Registration To Natural Language Understanding and Models of Communication (NLC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Continuous Speech Recognition Using LR Parsing With Effective Hypotheses Merging Mechanism
Sub Title (in English)
Keyword(1) Speech Recognition
Keyword(2) HMM
Keyword(3) LR Parser
Keyword(4) One-pass Search
Keyword(5) Finite State Automaton
1st Author's Name Tomokazu YAMADA
1st Author's Affiliation NTT Human Interface Labolatories()
2nd Author's Name Shoichi MATSUNAGA
2nd Author's Affiliation NTT Human Interface Labolatories
3rd Author's Name Shigeki SAGAYAMA
3rd Author's Affiliation NTT Human Interface Labolatories
Date 1996/12/13
Paper # NLC96-54,SP96-85
Volume (vol) vol.96
Number (no) 420
Page pp.pp.-
#Pages 6
Date of Issue