NDLI: Automatic Speech Recognition Based on Non-Uniform Error Criteria

Content Provider	IEEE Xplore Digital Library
Author	Qiang Fu Yong Zhao Biing-Hwang Juang
Copyright Year	2006
Abstract	The Bayes decision theory is the foundation of the classical statistical pattern recognition approach, with the expected error as the performance objective. For most pattern recognition problems, the “error” is conventionally assumed to be binary, i.e., 0 or 1, equivalent to error counting, independent of the specifics of the error made by the system. The term “error rate” is thus long considered the prevalent system performance measure. This performance measure, nonetheless, may not be satisfactory in many practical applications. In automatic speech recognition, for example, it is well known that some errors are more detrimental (e.g., more likely to lead to misunderstanding of the spoken sentence) than others. In this paper, we propose an extended framework for the speech recognition problem with non-uniform classification/recognition error cost which can be controlled by the system designer. In particular, we address the issue of system model optimization when the cost of a recognition error is class dependent. We formulate the problem in the framework of the minimum classification error (MCE) method, after appropriate generalization to integrate the class-dependent error cost into one consistent objective function for optimization. We present a variety of training scenarios for automatic speech recognition under this extended framework. Experimental results for continuous speech recognition are provided to demonstrate the effectiveness of the new approach.
Sponsorship	IEEE Signal Processing Society
Starting Page	780
Ending Page	793
Page Count	14
File Size	643374
File Format	PDF
ISSN	15587916
Volume Number	20
Issue Number	3
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-03-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Error analysis Training Speech recognition Cost function Measurement uncertainty minimum classification error cost (MCEC) Non-uniform error cost
Content Type	Text
Resource Type	Article
Subject	Acoustics and Ultrasonics Electrical and Electronic Engineering

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
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
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