NDLI: Using hidden Markov models for topic segmentation of meeting transcripts

Content Provider	IEEE Xplore Digital Library
Author	Sherman, M. Yang Liu
Copyright Year	2008
Description	Author affiliation: Behavioral & Brain Sci., Univ. of Texas at Dallas, Dallas, TX (Sherman, M.) \|\| Comput. Sci. Dept., Univ. of Texas at Dallas, Dallas, TX (Yang Liu)
Abstract	In this paper, we present a hidden Markov model (HMM) approach to segment meeting transcripts into topics. To learn the model, we use unsupervised learning to cluster the text segments obtained from topic boundary information. Using modified WinDiff and $P_{k}$ metrics, we demonstrate that an HMM outperforms LCSeg, a state-of-the-art lexical chain based method for topic segmentation using the ICSI meeting corpus. We evaluate the effect of language model order, the number of hidden states, and the use of stop words. Our experimental results show that a unigram LM is better than a trigram LM, using too many hidden states degrades topic segmentation performance, and that removing the stop words from the transcripts does not improve segmentation performance.
Starting Page	185
Ending Page	188
File Size	179125
Page Count	4
File Format	PDF
ISBN	9781424434718
DOI	10.1109/SLT.2008.4777871
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-12-15
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Machine learning algorithms Speech analysis Unsupervised learning Computer science Degradation LCSeg Meeting Transcript Topic Segmentation Hidden Markov models Coherence Broadcasting Feature extraction Hidden Markov Model Decision trees
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
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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8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
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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