NDLI: MODEL ADAPTATION FOR SENTENCE SEGMENTATION FROM SPEECH

Content Provider	IEEE Xplore Digital Library
Author	Cuendet, S. Hakkani-Tur, D. Tur, G.
Copyright Year	2006
Description	Author affiliation: Ecole Polytech. Fed. de Lausanne, Lausanne (Cuendet, S.)
Abstract	This paper analyzes various methods to adapt sentence segmentation models trained on conversational telephone speech (CTS) to meeting style conversations. The sentence segmentation model trained using a large amount of CTS data is used to improve the performance when various amounts of meeting data are available. We test the sentence segmentation performance on both reference and speech-to-text (STT) conditions on the ICSI MRDA meeting corpus using the switchboard CTS Corpus as the out-of-domain data. Results show that the sentence segmentation performance is significantly improved by the adapted classification model compared to the one obtained by using in-domain data only, independently of the amount of in-domain data used: 17.5% and 8.4% relative error reductions with only 1,000 and 3,000 in-domain sentences, respectively, and 3.7% relative error reduction with all in-domain data of 80,000 words.
Starting Page	102
Ending Page	105
File Size	210874
Page Count	4
File Format	PDF
ISBN	1424408725
DOI	10.1109/SLT.2006.326827
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-12-10
Publisher Place	Aruba
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computer science Speech analysis Adaptation model Hidden Markov models Speech recognition Broadcasting Telephony Labeling Speech processing Testing
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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