Decision tree based tone modeling with corrective feedbacks for automatic mandarin tone assessment

Hsien Cheng Liao*, Jiang Chun Chen, Sen Chia Chang, Ying Hua Guan, Chin Hui Lee

*此作品的通信作者

研究成果: 書貢獻/報告類型會議論文篇章

11 引文 斯高帕斯(Scopus)

摘要

We propose a novel decision tree based approach to Mandarin tone assessment. In most conventional computer assisted pronunciation training (CAPT) scenarios a tone production template is prepared as a reference with only numeric scores as feedbacks for tone learning. In contrast decision trees trained with an annotated tone-balanced corpus make use of a collection of questions related to important cues in categories of tone production. By traversing the corresponding paths and nodes associated with a test utterance a sequence of corrective comments can be generated to guide the learner for potential improvement. Therefore a detailed pronunciation indication or a comparison between two paths can be provided to learners which are usually unavailable in score-based CAPT systems.

原文英語
主出版物標題Proceedings of the 11th Annual Conference of the International Speech Communication Association, INTERSPEECH 2010
發行者International Speech Communication Association
頁面602-605
頁數4
出版狀態已發佈 - 2010

出版系列

名字Proceedings of the 11th Annual Conference of the International Speech Communication Association, INTERSPEECH 2010

ASJC Scopus subject areas

  • 語言與語言學
  • 言語和聽力

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