Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/90658
Title: A two-channel training algorithm for hidden Markov model to identify visual speech elements
Authors: Foo, Say Wei
Yong, Lian
Dong, Liang
Keywords: DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
Issue Date: 2003
Source: Foo, S. W., Yong, L., & Dong, L. (2003). A two-channel training algorithm for hidden Markov model to identify visual speech elements. In Proceedings of the International Symposium on Circuits and Systems 2003: (pp.572-575). Singapore.
Abstract: A novel two-channel algorithm is proposed in this paper for discriminative training of Hidden Markov Models (HMMs). It adjusts the symbol emission coefficients of an existing HMM to maximize the separable distance between a pair of confusable training samples. The method is applied to identify the visemes of visual speech. The results indicate that the two-channel training method provides better accuracy on separating similar visemes than the conventional Baum-Welch estimation.
URI: https://hdl.handle.net/10356/90658
http://hdl.handle.net/10220/5843
DOI: http://dx.doi.org/10.1109/ISCAS.2003.1206038
Rights: © IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. http://www.ieee.org/portal/site.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Conference Papers

Files in This Item:
File Description SizeFormat 
C69-II_572-ISCAS2003DL.pdfPublished version241.34 kBAdobe PDFThumbnail
View/Open

Google ScholarTM

Check

Altmetric

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.