摘要
This chapter presents an efficient approach to personalized pronunciation assessment of Taiwaneseaccented English. The main goal of this study is to detect frequently occurring mispronunciation patterns of Taiwanese-accented English instead of scoring English pronunciations directly. The proposed assessment help quickly discover personalized mispronunciations of a student, thus English teachers can spend more time on teaching or rectifying students' pronunciations. In this approach, an unsupervised model adaptation method is performed on the universal acoustic models to recognize the speech of a specific speaker with mispronunciations and Taiwanese accent. A dynamic sentence selection algorithm, considering the mutual information of the related mispronunciations, is proposed to choose a sentence containing the most undetected mispronunciations in order to quickly extract personalized mispronunciations. The experimental results show that the proposed unsupervised adaptation approach obtains an accuracy improvement of about 2.1% on the recognition of Taiwanese-accented English speech.
原文 | English |
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主出版物標題 | Multidisciplinary Computational Intelligence Techniques |
主出版物子標題 | Applications in Business, Engineering, and Medicine |
發行者 | IGI Global |
頁面 | 12-30 |
頁數 | 19 |
ISBN(列印) | 9781466618305 |
DOIs | |
出版狀態 | Published - 2012 |
All Science Journal Classification (ASJC) codes
- 一般電腦科學