Automatic speech recognition and dependency network to identification of articulation error patterns

Yeou Jiunn Chen, Jiunn Liang Wu, Hui Mei Yang

研究成果: Conference contribution

摘要

Articulation errors will seriously reduce speech intelligibility and the ease of spoken communication. Typically, a language therapist uses his or her clinical experience to identify articulation error patterns, a time-consuming and expensive process. This paper presents a novel automatic approach to identifying articulation error patterns and providing error information of pronunciation to assist the linguistic therapist. A photo naming task is used to capture examples of an individual's articulation patterns. The collected speech is automatically segmented and labeled by a speech recognizer. The recognizer's pronunciation confusion network is adapted to improve the accuracy of the speech recognizer. The modified dependency network and a multiattribute decision model are applied to identify articulation error patterns. Experimental results reveal the usefulness of the proposed method and system.

原文English
主出版物標題2008 International Joint Conference on Neural Networks, IJCNN 2008
頁面4009-4013
頁數5
DOIs
出版狀態Published - 2008 十一月 24
事件2008 International Joint Conference on Neural Networks, IJCNN 2008 - Hong Kong, China
持續時間: 2008 六月 12008 六月 8

出版系列

名字Proceedings of the International Joint Conference on Neural Networks

Other

Other2008 International Joint Conference on Neural Networks, IJCNN 2008
國家China
城市Hong Kong
期間08-06-0108-06-08

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence

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  • 引用此

    Chen, Y. J., Wu, J. L., & Yang, H. M. (2008). Automatic speech recognition and dependency network to identification of articulation error patterns. 於 2008 International Joint Conference on Neural Networks, IJCNN 2008 (頁 4009-4013). [4634374] (Proceedings of the International Joint Conference on Neural Networks). https://doi.org/10.1109/IJCNN.2008.4634374