Improving Mispronunciation Detection for Non-Native Learners with Multisource Information and LSTM-Based Deep Models-Reference-Cited by-同舟云学术

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Improving Mispronunciation Detection for Non-Native Learners with Multisource Information and LSTM-Based Deep Models

Published:2017-08-20 Issue: Volume: Page:
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Container-title:Interspeech 2017
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Author:

Li Wei,Chen Nancy F.,Siniscalchi Sabato Marco,Lee Chin-Hui

Publisher

ISCA

Cited by 21 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Communication-Oriented Automatic Assessment System for Accented Spoken Chinese in Read-Aloud Tasks;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

2. Mispronunciation detection and diagnosis using deep neural networks: a systematic review;Multimedia Tools and Applications;2024-01-09

3. Hierarchical Pronunciation Assessment with Multi-Aspect Attention;ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2023-06-04

4. Review of Recent Systems for Detecting and Diagnosing Pronunciation Errors;2023 IEEE International Conference on Advanced Systems and Emergent Technologies (IC_ASET);2023-04-29

5. Mispronunciation Detection Using Neural Networks for Second Language Learners;Advances in Educational Technologies and Instructional Design;2023-01-13

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