The effectiveness of corpus-induced dependency grammars for post-processing speech

M. P. Harper; C. M. White; W. Wang; M. T. Johnson; R. A. Helzerman

The effectiveness of corpus-induced dependency grammars for post-processing speech

M. P. Harper
, C. M. White
, W. Wang
, M. T. Johnson
, R. A. Helzerman

Research output: Contribution to conference › Paper › peer-review

5 Scopus citations

Abstract

This paper investigates the impact of Constraint Dependency Grammars (CDG) on the accuracy of an integrated speech recognition and CDG parsing system. We compare a conventional CDG with CDGs that are induced from annotated sentences and template-expanded sentences. The grammars are evaluated on parsing speed, precision/coverage, and improvement of word and sentence accuracy of the integrated system. Sentence-derived CDGs significantly improve recognition accuracy over the conventional CDG but are less general. Expanding the sentences with templates provides us with a mechanism for increasing the coverage of the grammar with only minor reductions in recognition accuracy.

Original language	English
Pages	102-109
Number of pages	8
State	Published - 2000
Event	1st Meeting of the North American Chapter of the Association for Computational Linguistics, NAACL 2000 - Seattle, United States Duration: Apr 29 2000 → May 4 2000

Conference

Conference	1st Meeting of the North American Chapter of the Association for Computational Linguistics, NAACL 2000
Country/Territory	United States
City	Seattle
Period	4/29/00 → 5/4/00

Bibliographical note

Publisher Copyright:
© ANLP 2000. All rights reserved.

Funding

This research was supported by grants from Intel, Purdue Research Foundation, and National Science Foundation IRI 97-04358, CDA 96-17388, and #9980054-BCS.

Funders	Funder number
U.S. Department of Energy Chinese Academy of Sciences Guangzhou Municipal Science and Technology Project Oak Ridge National Laboratory Extreme Science and Engineering Discovery Environment National Science Foundation National Energy Research Scientific Computing Center National Natural Science Foundation of China	CDA 96-17388, 9980054-BCS, IRI 97-04358
U.S. Department of Energy Chinese Academy of Sciences Guangzhou Municipal Science and Technology Project Oak Ridge National Laboratory Extreme Science and Engineering Discovery Environment National Science Foundation National Energy Research Scientific Computing Center National Natural Science Foundation of China
Intel Corporation
Purdue University Research Foundation

ASJC Scopus subject areas

Language and Linguistics
Computer Science Applications
Linguistics and Language

Cite this

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abstract = "This paper investigates the impact of Constraint Dependency Grammars (CDG) on the accuracy of an integrated speech recognition and CDG parsing system. We compare a conventional CDG with CDGs that are induced from annotated sentences and template-expanded sentences. The grammars are evaluated on parsing speed, precision/coverage, and improvement of word and sentence accuracy of the integrated system. Sentence-derived CDGs significantly improve recognition accuracy over the conventional CDG but are less general. Expanding the sentences with templates provides us with a mechanism for increasing the coverage of the grammar with only minor reductions in recognition accuracy.",

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AU - White, C. M.

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AU - Johnson, M. T.

AU - Helzerman, R. A.

PY - 2000

Y1 - 2000

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AB - This paper investigates the impact of Constraint Dependency Grammars (CDG) on the accuracy of an integrated speech recognition and CDG parsing system. We compare a conventional CDG with CDGs that are induced from annotated sentences and template-expanded sentences. The grammars are evaluated on parsing speed, precision/coverage, and improvement of word and sentence accuracy of the integrated system. Sentence-derived CDGs significantly improve recognition accuracy over the conventional CDG but are less general. Expanding the sentences with templates provides us with a mechanism for increasing the coverage of the grammar with only minor reductions in recognition accuracy.

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ER -

The effectiveness of corpus-induced dependency grammars for post-processing speech

Abstract

Conference

Bibliographical note

Funding

ASJC Scopus subject areas

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Cite this