Efficient error correction for speech systems using constrained re-recognition

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.

Bibliographic Details
Main Author: Yu, Gregory T
Other Authors: James R. Glass and Lee Hetherington.
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2009
Subjects:
Online Access:http://hdl.handle.net/1721.1/46533
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author Yu, Gregory T
author2 James R. Glass and Lee Hetherington.
author_facet James R. Glass and Lee Hetherington.
Yu, Gregory T
author_sort Yu, Gregory T
collection MIT
description Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.
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spelling mit-1721.1/465332019-04-12T16:09:12Z Efficient error correction for speech systems using constrained re-recognition Yu, Gregory T James R. Glass and Lee Hetherington. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008. Includes bibliographical references (p. 71-75). Efficient error correction of recognition output is a major barrier in the adoption of speech interfaces. This thesis addresses this problem through a novel correction framework and user interface. The system uses constraints provided by the user to enhance re-recognition, correcting errors with minimal user effort and time. In our web interface, users listen to the recognized utterance, marking incorrect words as they hear them. After they have finished marking errors, they submit the edits back to the speech recognizer where it is merged with previous edits and then converted into a finite state transducer. This FST, modeling the regions of correct and incorrect words in the recognition output, is then composed with the recognizer's language model and the utterance is re-recognized. We explored the use of our error correction technique in both the lecture and restaurant domain, evaluating the types of errors and the correction performance in each domain. With our system, we have found significant improvements over other error correction techniques such as n-best lists, re-speaking or verbal corrections, and retyping in terms of actions per correction step, corrected output rate, and ease of use. by Gregory T. Yu. M.Eng. 2009-08-26T16:44:13Z 2009-08-26T16:44:13Z 2008 2008 Thesis http://hdl.handle.net/1721.1/46533 416577106 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 75 p. application/pdf Massachusetts Institute of Technology
spellingShingle Electrical Engineering and Computer Science.
Yu, Gregory T
Efficient error correction for speech systems using constrained re-recognition
title Efficient error correction for speech systems using constrained re-recognition
title_full Efficient error correction for speech systems using constrained re-recognition
title_fullStr Efficient error correction for speech systems using constrained re-recognition
title_full_unstemmed Efficient error correction for speech systems using constrained re-recognition
title_short Efficient error correction for speech systems using constrained re-recognition
title_sort efficient error correction for speech systems using constrained re recognition
topic Electrical Engineering and Computer Science.
url http://hdl.handle.net/1721.1/46533
work_keys_str_mv AT yugregoryt efficienterrorcorrectionforspeechsystemsusingconstrainedrerecognition