정제 알고리즘을 이용한 한국인 화자의 영어 발화 자동 진단 시스템

Automatic Pronunciation Diagnosis System of Korean Students' English Using Purification Algorithm

We propose an automatic pronunciation diagnosis system to evaluate the pronunciation of a foreign language without the uttered text. We recorded English utterances spoken by native and Korean speakers, and utterances spoken by Koreans are evaluated by native speakers based on three criteria: fluency, accuracy of phones and intonation. The system evaluates the utterances of test Korean speakers based on the differences of log-likelihood given two models: one is trained by English speech uttered by native speakers, and the other is trained by English speech uttered by Korean speakers. We also applied purification algorithm to increase class differentiability. The purification can detect and eliminate the non-speech frames such as short pauses, occlusive silences that do not help to discriminate between utterances. As the results, our proposed system has higher correlation with the human scores than the baseline system.