상세정보
학술지
Automatic Proficiency Assessment of Korean Speech Read Aloud by Non-natives using Bidirectional LSTM-based Speech Recognition
- 발행일
- 202010
- 출처
- ETRI Journal, v.42 no.5, pp.761-772
- ISSN
- 1225-6463
- 출판사
- 한국전자통신연구원 (ETRI)
- 협약과제
- 19HS2500, 준지도학습형 언어지능 원천기술 및 이에 기반한 외국인 지원용 한국어 튜터링 서비스 개발, 이윤근
- 초록
- This paper presents an automatic proficiency assessment method for a non-native Korean read utterance using bidirectional long short?뱓erm memory (BLSTM)?밷ased acoustic models (AMs) and speech data augmentation techniques. Specifically, the proposed method considers two scenarios, with and without prompted text. The proposed method with the prompted text performs (a) a speech feature extraction step, (b) a forced-alignment step using a native AM and non-native AM, and (c) a linear regression?밷ased proficiency scoring step for the five proficiency scores. Meanwhile, the proposed method without the prompted text additionally performs Korean speech recognition and a subword un-segmentation for the missing text. The experimental results indicate that the proposed method with prompted text improves the performance for all scores when compared to a method employing conventional AMs. In addition, the proposed method without the prompted text has a fluency score performance comparable to that of the method with prompted text.
- KSP 제안 키워드
- Assessment method, Augmentation techniques, Data Augmentation, Korean speech, Linear regression, Proficiency assessment, acoustic model, bidirectional LSTM, speech feature extraction, speech recognition
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