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학술지 Automatic Proficiency Assessment of Korean Speech Read Aloud by Non-natives using Bidirectional LSTM-based Speech Recognition
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저자
오유리, 박기영, 전형배, 박전규
발행일
202010
출처
ETRI Journal, v.42 no.5, pp.761-772
ISSN
1225-6463
출판사
한국전자통신연구원 (ETRI)
DOI
https://dx.doi.org/10.4218/etrij.2019-0400
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.
키워드
automatic speech recognition (ASR) for a non-native Korean utterance, bidirectional long short?뱓erm memory (BLSTM)?밷ased acoustic models (AMs), speech data augmentation, spoken computer-assisted language learning (CALL), spoken proficiency assessment
KSP 제안 키워드
Assessment method, Augmentation techniques, Data Augmentation, Korean speech, Linear regression, Proficiency assessment, acoustic model, automatic speech recognition(ASR), bidirectional LSTM, computer assisted language learning, speech feature extraction
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