Continuous Speech Recognition Using a Dependency Grammar and Phoneme-Based HMMs

Sho-ichi MATSUNAGA; Shigeru HOMMA; Shigeki SAGAYAMA; Sadaoki FURUI

Continuous Speech Recognition Using a Dependency Grammar and Phoneme-Based HMMs

Sho-ichi MATSUNAGA, Shigeru HOMMA, Shigeki SAGAYAMA, Sadaoki FURUI

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This paper describes two Japanese continuous speech recognition systems (system-1 and system-2) based on phoneme-based HMMs and a two-level grammar approach. Two grammars are an intra-phrase transition network grammar for phrase recognition, and an inter-phrase dependency grammar for sentence recognition. A joint score, combining acoustic likelihood and linguistic certainty factors derived from phonemebased HMMs and dependency rules, is maximized to obtain the best sentence recognition results. System-1 is tuned for sentences uttered phrase-by-phrase and system-2 is tuned for sentence utterances, to make the amount of computation practical. In system-1, two efficient parsing algorithms are used for each grammar. They are a bi-directional network parser and a breadth-first dependency parser. With the phrase-network parser, input phrase utterances are parsed bi-directionally both left-to-right and right-to-left, and optimal Viterbi paths are found along which the accumulated phonetic likelihood is maximized. The dependency parser utilizes efficient breadth-first search and beam search algorithms. For system-2, we have extended the dependency analysis algorithm for sentence utterances, using a technique for detecting most-likely multi-phrase candidates based on the Viterbi phrase alignment. Where the perplexity of the phrase syntax is 40, system-1 and system-2 increase phrase recognition performance in the sentence by approximately 6% and 14%, showing the effectiveness of semantic dependency analysis.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E74-A No.7 pp.1826-1833

Publication Date: 1991/07/25

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Type of Manuscript: Special Section PAPER (Special Issue on Continuous Speech Recognition and Understanding)

Category: Continuous Speech Recognition

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Sho-ichi MATSUNAGA
Shigeru HOMMA
Shigeki SAGAYAMA
Sadaoki FURUI

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Sho-ichi MATSUNAGA, Shigeru HOMMA, Shigeki SAGAYAMA, Sadaoki FURUI, "Continuous Speech Recognition Using a Dependency Grammar and Phoneme-Based HMMs" in IEICE TRANSACTIONS on Fundamentals, vol. E74-A, no. 7, pp. 1826-1833, July 1991, doi: .
Abstract: This paper describes two Japanese continuous speech recognition systems (system-1 and system-2) based on phoneme-based HMMs and a two-level grammar approach. Two grammars are an intra-phrase transition network grammar for phrase recognition, and an inter-phrase dependency grammar for sentence recognition. A joint score, combining acoustic likelihood and linguistic certainty factors derived from phonemebased HMMs and dependency rules, is maximized to obtain the best sentence recognition results. System-1 is tuned for sentences uttered phrase-by-phrase and system-2 is tuned for sentence utterances, to make the amount of computation practical. In system-1, two efficient parsing algorithms are used for each grammar. They are a bi-directional network parser and a breadth-first dependency parser. With the phrase-network parser, input phrase utterances are parsed bi-directionally both left-to-right and right-to-left, and optimal Viterbi paths are found along which the accumulated phonetic likelihood is maximized. The dependency parser utilizes efficient breadth-first search and beam search algorithms. For system-2, we have extended the dependency analysis algorithm for sentence utterances, using a technique for detecting most-likely multi-phrase candidates based on the Viterbi phrase alignment. Where the perplexity of the phrase syntax is 40, system-1 and system-2 increase phrase recognition performance in the sentence by approximately 6% and 14%, showing the effectiveness of semantic dependency analysis.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e74-a_7_1826/_p

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@ARTICLE{e74-a_7_1826,
author={Sho-ichi MATSUNAGA, Shigeru HOMMA, Shigeki SAGAYAMA, Sadaoki FURUI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Continuous Speech Recognition Using a Dependency Grammar and Phoneme-Based HMMs},
year={1991},
volume={E74-A},
number={7},
pages={1826-1833},
abstract={This paper describes two Japanese continuous speech recognition systems (system-1 and system-2) based on phoneme-based HMMs and a two-level grammar approach. Two grammars are an intra-phrase transition network grammar for phrase recognition, and an inter-phrase dependency grammar for sentence recognition. A joint score, combining acoustic likelihood and linguistic certainty factors derived from phonemebased HMMs and dependency rules, is maximized to obtain the best sentence recognition results. System-1 is tuned for sentences uttered phrase-by-phrase and system-2 is tuned for sentence utterances, to make the amount of computation practical. In system-1, two efficient parsing algorithms are used for each grammar. They are a bi-directional network parser and a breadth-first dependency parser. With the phrase-network parser, input phrase utterances are parsed bi-directionally both left-to-right and right-to-left, and optimal Viterbi paths are found along which the accumulated phonetic likelihood is maximized. The dependency parser utilizes efficient breadth-first search and beam search algorithms. For system-2, we have extended the dependency analysis algorithm for sentence utterances, using a technique for detecting most-likely multi-phrase candidates based on the Viterbi phrase alignment. Where the perplexity of the phrase syntax is 40, system-1 and system-2 increase phrase recognition performance in the sentence by approximately 6% and 14%, showing the effectiveness of semantic dependency analysis.},
keywords={},
doi={},
ISSN={},
month={July},}

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TY - JOUR
TI - Continuous Speech Recognition Using a Dependency Grammar and Phoneme-Based HMMs
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1826
EP - 1833
AU - Sho-ichi MATSUNAGA
AU - Shigeru HOMMA
AU - Shigeki SAGAYAMA
AU - Sadaoki FURUI
PY - 1991
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E74-A
IS - 7
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - July 1991
AB - This paper describes two Japanese continuous speech recognition systems (system-1 and system-2) based on phoneme-based HMMs and a two-level grammar approach. Two grammars are an intra-phrase transition network grammar for phrase recognition, and an inter-phrase dependency grammar for sentence recognition. A joint score, combining acoustic likelihood and linguistic certainty factors derived from phonemebased HMMs and dependency rules, is maximized to obtain the best sentence recognition results. System-1 is tuned for sentences uttered phrase-by-phrase and system-2 is tuned for sentence utterances, to make the amount of computation practical. In system-1, two efficient parsing algorithms are used for each grammar. They are a bi-directional network parser and a breadth-first dependency parser. With the phrase-network parser, input phrase utterances are parsed bi-directionally both left-to-right and right-to-left, and optimal Viterbi paths are found along which the accumulated phonetic likelihood is maximized. The dependency parser utilizes efficient breadth-first search and beam search algorithms. For system-2, we have extended the dependency analysis algorithm for sentence utterances, using a technique for detecting most-likely multi-phrase candidates based on the Viterbi phrase alignment. Where the perplexity of the phrase syntax is 40, system-1 and system-2 increase phrase recognition performance in the sentence by approximately 6% and 14%, showing the effectiveness of semantic dependency analysis.
ER -