NDLI: Development and evaluation of discriminative training algorithm using HMMs with mixtures of linear trended functions

Content Provider	IEEE Xplore Digital Library
Author	Chengalvarayan, R.
Copyright Year	1997
Description	Author affiliation: Bell Labs., Lucent Technol., Naperville, IL, USA (Chengalvarayan, R.)
Abstract	We extend the maximum likelihood (ML) training algorithm to the minimum classification error (MCE) training algorithm for discriminatively estimating the state-dependent and mixture-dependent polynomial coefficients in the linear trended HMM. The main motivation of this extension is a greater degree of freedom in the modeled trajectory space associated with the trended HMM than that with the conventional, stationary-state HMM which describes only the (piecewise) constant "degraded trajectories" in the observation data. Hence, the discriminative training implemented for the trended HMM should have a strong power to disambiguate the observational trajectories generated from nonstationary sources corresponding to different speech classes. The properties of the MCE formulation for training the trended HMM is analyzed by examining the goodness-of-fit of the raw speech data to the polynomial trajectories in the model. Phonetic classification results are reported which demonstrate consistent performance improvements with use of the MCE-trained trended HMM both over the regular ML-trained trended HMM and over the MCE-trained stationary-state HMM.
Starting Page	1011
Ending Page	1015
File Size	564324
Page Count	5
File Format	PDF
ISBN	0780336763
DOI	10.1109/ICICS.1997.652133
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1997-09-12
Publisher Place	Singapore
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Hidden Markov models Speech analysis Trajectory Maximum likelihood estimation Polynomials State estimation Space stations Speech processing Power generation Speech recognition
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
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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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