Analysis of Mispronunciation Detection and Diagnosis Based on Conventional Deep Learning Techniques
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-9442-7_31
Reference50 articles.
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2. Qian X-J, Meng H, Soong F (2010) Capturing L2 segmental mispronunciations with joint-sequence models in computer-aided pronunciation training (CAPT). In: Proceedings of 7th international symposium conference on spoken language processing, pp 84–88. https://doi.org/10.1109/ISCSLP.2010.5684845
3. Mao S, Wu Z, Li X, Li R, Wu X, Meng H (2018) Integrating articulatory features into acoustic-phonemic model for mispronunciation detection and diagnosis in L2 English speech. https://doi.org/10.1109/ICME.2018.8486462
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5. Yang X, Audhkhasi K, Rosenberg A, Thomas S, Ramabhadran B, Hasegawa-Johnson M (2018) Joint modeling of accents and acoustics for multi-accent speech recognition. Proc ICASSP: 1–5. https://doi.org/10.1109/ICASSP.2018.8462557
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