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Disentangling the Contribution of Non-native Speech in Automated Pronunciation Assessment.

, , , , , , and . INTERSPEECH, page 954-958. ISCA, (2023)

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Disentangling the Contribution of Non-native Speech in Automated Pronunciation Assessment., , , , , , and . INTERSPEECH, page 954-958. ISCA, (2023)Capturing L1 Influence on L2 Pronunciation by Simulating Perceptual Space Using Acoustic Features., , and . INTERSPEECH, page 2648-2652. ISCA, (2019)Automatic detection of rhythmic patterns in native and L2 speech: Chinese, Japanese, and Japanese L2 Chinese., , , and . ISCSLP, page 1-4. IEEE, (2016)Automatic Assessment and Error Detection of Shadowing Speech: Case of English Spoken by Japanese Learners., , , , , , and . INTERSPEECH, page 3142-3146. ISCA, (2016)Modeling Clinical Empathy in Narrative Essays., , , , and . ICSC, page 215-220. IEEE, (2021)Acoustic correlates and gender effects in production and perception of Japanese polite speech., , , , and . ISCSLP, page 1-5. IEEE, (2016)Phonetic and Prosody-aware Self-supervised Learning Approach for Non-native Fluency Scoring., , , , , and . INTERSPEECH, page 949-953. ISCA, (2023)Cross-language comparison of F0 range in speakers of native Chinese, native Japanese and Chinese L2 of Japanese: Preliminary results of a corpus-based analysis., , and . ISCSLP, page 241-244. IEEE, (2014)Leveraging Phone-Level Linguistic-Acoustic Similarity For Utterance-Level Pronunciation Scoring., , , , , , and . ICASSP, page 1-5. IEEE, (2023)An ASR-Free Fluency Scoring Approach with Self-Supervised Learning., , , , , , and . ICASSP, page 1-5. IEEE, (2023)