NDLI: Discriminative transformations of speech features based on minimum classification error

Content Provider	IEEE Xplore Digital Library
Author	Zamani, Behzad Akbari, Ahmad Nasersharif, Babak Jalalvand, Azarakhsh
Copyright Year	2011
Description	Author affiliation: Audio & Speech Processing Lab, Iran University of Science & Technology, Iran (Zamani, Behzad; Akbari, Ahmad; Nasersharif, Babak; Jalalvand, Azarakhsh) Feature extraction is an important step in pattern classification and speech recognition. Extracted features should discriminate classes from each other while being robust to the environmental conditions such as noise. For this purpose, some transformations are applied to features. In this paper, we propose a framework to improve independent feature transformations such as PCA (Principal Component Analysis), and HLDA (Heteroscedastic LDA) using the minimum classification error criterion. In this method, we modify full transformation matrices such that classification error is minimized for mapped features. We do not reduce feature vector dimension in this mapping. The proposed methods are evaluated for continuous phoneme recognition on clean and noisy TIMIT. Experimental results show that our proposed methods improve performance of PCA, and HLDA transformation for MFCC in both clean and noisy conditions.
Sponsorship	IEEE Iran Sect.
Starting Page	1
Ending Page	5
File Size	278519
Page Count	5
File Format	PDF
ISBN	9781457707308
ISSN	01678655
e-ISBN	9789644634284
DOI	10.1016/j.patrec.2011.01.017
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-05-17
Publisher Place	Iran
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	AmirKabir Univ of Tech
Subject Keyword	Training Feature transformation Noise Minimum classification error Hidden Markov models Speech recognition Feature extraction Cost function Principal component analysis
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Signal Processing Computer Vision and Pattern Recognition Software

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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