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Journal Article
Automatic proficiency assessment of Korean speech read aloud by non‐natives using bidirectional LSTM‐based speech recognition
- Authors
- Yoo Rhee Oh, Kiyoung Park, Hyung-Bae Jeon, Jeon Gue Park
- Issue Date
- 2020-10
- Citation
- ETRI Journal, v.42, no.5, pp.761-772
- ISSN
- 1225-6463
- Publisher
- 한국전자통신연구원 (ETRI)
- Language
- English
- Type
- Journal Article
- Abstract
- 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.
This work is distributed under the term of Korea Open Government License (KOGL)
(Type 4: : Type 1 + Commercial Use Prohibition+Change Prohibition)
(Type 4: : Type 1 + Commercial Use Prohibition+Change Prohibition)
