NDLI: Multiple mixture segmental HMM and its applications

Content Provider	IEEE Xplore Digital Library
Author	Bing Xiang Berger, T.
Copyright Year	2001
Description	Author affiliation: Sch. of Electr. Eng. & Comput. Eng., Cornell Univ., Ithaca, NY, USA (Bing Xiang)
Abstract	A multiple mixture segmental hidden Markov model (MMSHMM) is presented. This model is extended from the linear probabilistic-trajectory segmental HMM. Each segment is characterized by a linear trajectory with slope and mid-point parameters, and also the residual error covariances around the trajectory, so that both extra-segmental and intra-segmental variation are represented. Instead of modeling single distribution for each model parameter as earlier work, we use multiple mixture components for model parameters to represent the variability due to the variation within each speaker and also the differences between speakers. This model is evaluated on two applications. One is a phonetic classification task with TIMIT corpus, which shows that MMSHMM has advantages over conventional HMM. Another one is a speaker-independent keyword spotting task with the Road Rally database. By rescoring putative events hypothesized by a primary HMM keyword spotter, the experiments show that the performance is improved through distinguishing true hits from false alarms.
Sponsorship	IEEE Signal Process. Soc
Starting Page	509
Ending Page	512
File Size	420256
Page Count	4
File Format	PDF
ISBN	0780370414
ISSN	15206149
DOI	10.1109/ICASSP.2001.940879
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2001-05-07
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Hidden Markov models Databases Speech recognition Application software Humans Production systems Error analysis Statistical distributions Gaussian distribution Probability distribution
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
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