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This paper proposes a method for automatic pronunciation assessment of Korean spoken by L2 learners by selecting the best feature set from a collection of the most well-known features in the literature. The L2 Korean Speech Corpus is used for assessment modeling, where the native languages of the L2 learners are English, Chinese, Japanese, Russian, and Mongolian. In our system, learners' speech is...
This paper aims to improve the performance of automatic pronunciation generation of foreign loanwords in Korean by using phonological knowledge and syllable-based segmentation. The loanword text corpus used for our experiment consists of 16.6K words extracted from the frequently used words in set-top box, music, and POI domains. At first, pronunciations of loanwords in Korean are obtained by manual...
The increasing demand for learning Korean as a foreign language yields a strong need for a CAPT system that is able to provide automatic tutoring. However, there is limited research on Korean pronunciation produced by non-natives. As a preliminary research towards developing a CAPT system for Chinese learners of Korean, we survey key findings of previous studies. And then, based on corpus analysis,...
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