@inproceedings{c9b872e2dc5849c08dd5a4b605621245,
title = "Decision tree based tone modeling with corrective feedbacks for automatic mandarin tone assessment",
abstract = "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.",
keywords = "Computer aided language learning, Computer assisted pronunciation training, Feedback, Tone assessment",
author = "Liao, {Hsien Cheng} and Chen, {Jiang Chun} and Chang, {Sen Chia} and Guan, {Ying Hua} and Lee, {Chin Hui}",
note = "Funding Information: This study is partially supported by Project 9352MD3100 and conducted at ITRI under the sponsorship of the Ministry of Economic Affairs, Taiwan.",
year = "2010",
language = "English",
series = "Proceedings of the 11th Annual Conference of the International Speech Communication Association, INTERSPEECH 2010",
publisher = "International Speech Communication Association",
pages = "602--605",
booktitle = "Proceedings of the 11th Annual Conference of the International Speech Communication Association, INTERSPEECH 2010",
}