NDLI: An Articulation Training System with Intelligent Interface and Multimode Feedbacks to Articulation Disorders

Content Provider	IEEE Xplore Digital Library
Author	Yeou-Jiunn Chen Jiunn-Liang Wu Hui-Mei Yang Chung-Hsien Wu Chih-Chang Chen Shan-Shan Ju
Copyright Year	2009
Abstract	Articulation training with many kinds of stimulus and messages such as visual, voice, and articulatory information can teach user to pronounce correctly and improve user’s articulatory ability. In this paper, an articulation training system with intelligent interface and multimode feedbacks is proposed to improve the performance of articulation training. Clinical knowledge of speech evaluation is used to design the dependent network. Then, automatic speech recognition with dependent network is applied to identify the pronunciation errors. Besides, hierarchical Bayesian network is proposed to recognize user’s emotion from speeches. With the information of pronunciation errors and user’s emotional state, the articulation training sentences can be dynamically selected. Finally, a 3D facial animation is provided to teach users to pronounce a sentence by using speech, lip motion, and tongue motion. Experimental results reveal the usefulness of proposed method and system.
Starting Page	3
Ending Page	6
File Size	400360
Page Count	4
File Format	PDF
ISBN	9780769539041
DOI	10.1109/IALP.2009.10
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-12-07
Publisher Place	Singapore
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Industrial training Emotion recognition Tongue Hospitals Bayesian methods Feedback Computer errors Facial animation Intelligent systems Automatic speech recognition
Content Type	Text
Resource Type	Article

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