NDLI: Triseme decision trees in the continuous speech recognition system for a talking head

Content Provider	IEEE Xplore Digital Library
Author	Dong-Mei Jiang Lei Xie Ravyse, I. Rong-Chun Zhao Sahli, H. Cornelis, J.
Copyright Year	2002
Description	Author affiliation: Dept. Comput. Sci. & Eng., Northwestern Polytech. Univ., Xi'an, China (Dong-Mei Jiang; Lei Xie)
Abstract	In this paper, we present a viseme (the basic speech units In the visual domain) based continuous speech recognition system, which segments speech into viseme sequences with timing boundaries to drive a talking head. In the viseme Hidden Markov Model (HMM) training, the instances of a viseme with different contexts are formulated as trisemes. Based on the mouth shape parameters Liprounding and the defined viseme similarity weight (VSW) from the 3D viseme facial models, 166 questions concerning the viseme contexts are designed to build triseme decision trees to tie the states of the trisemes with similar contexts, so that they can share the same parameters. To evaluate the system performance, the image related measurements are also taken to evaluate the resulting viseme sequences, with 'jerky instances' in Liprounding and VSW graphs evaluating their smoothness. Results show that compared to the phoneme based system, the tied-state triseme based speech recognition system gives talking head animation with smoother and more plausible mouth shapes.
Sponsorship	Hebei Univ. IEEE Syst., Man & Cybernetics Tech. Committe on Cybernetics
Starting Page	2097
Ending Page	2101
File Size	322927
Page Count	5
File Format	PDF
ISBN	0780375084
DOI	10.1109/ICMLC.2002.1175408
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-11-04
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Decision trees Speech recognition Head Hidden Markov models Mouth Shape Timing Context modeling System performance Animation
Content Type	Text
Resource Type	Article

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