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A Study of Articulatory Features Based Detection of Mandrain Pronunciation Erroneous Tendency for Automatic Annotation
WEI Xing, WANG Wei, CHEN Jingping, XIE Yanlu, ZHANG Jinsong
Acta Scientiarum Naturalium Universitatis Pekinensis    2018, 54 (2): 243-248.   DOI: 10.13209/j.0479-8023.2017.152
Abstract836)   HTML3)    PDF(pc) (1670KB)(411)       Save

For the purpose of relieving the time cost and inconformity in annotation, the authors use an articulatory features based mispronunciation detection system to give an Top-N feedback and use this feedback to assist manual annotation. As a result, the consistency rate of phoneme labels in proposed system increases from 80.7% to 92.48%. In addition, the time cost for annotating each sentence reduce from 10 to 3 minutes. The results indicate that proposed automatic annotation system is practical, and there is also a room for further improvement.

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