Decision Tree Based Tone Modeling with Corrective Feedbacks for Automatic Mandarin Tone Assessment.

dc.contributor國立臺灣師範大學應用華語文學系zh_tw
dc.contributor.authorLiao, H.C.en_US
dc.contributor.authorChen, J.C.en_US
dc.contributor.authorChang, S.C.en_US
dc.contributor.authorGuan, Y. H.en_US
dc.contributor.authorLee, C.H.en_US
dc.date.accessioned2014-10-30T09:27:06Z
dc.date.available2014-10-30T09:27:06Z
dc.date.issued2010-09-30zh_TW
dc.description.abstractWe 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.en_US
dc.identifierntnulib_tp_H0105_02_002zh_TW
dc.identifier.isbn978-161-782-123-3zh_TW
dc.identifier.urihttp://rportal.lib.ntnu.edu.tw/handle/20.500.12235/31358
dc.languageenzh_TW
dc.relationThe proceedings of Interspeech 2010(pp.602-605), Makuhari, Chiba, Japan.en_US
dc.titleDecision Tree Based Tone Modeling with Corrective Feedbacks for Automatic Mandarin Tone Assessment.en_US

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