A Transfer Learning Approach for Pronunciation Scoring
Author:
Affiliation:
1. Universidad de Buenos Aires (UBA),FCEyN,Departamento de Computación,Argentina
2. Instituto de Investigación en Ciencias de la Computación (ICC),CONICET-UBA,Argentina
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9745891/9746004/09747727.pdf?arnumber=9747727
Reference27 articles.
1. A transfer learning approach to goodness of pronunciation based automatic mispronunciation detection
2. Transfer Learning based Non-native Acoustic Modeling for Pronunciation Error Detection
3. Context-Aware Goodness of Pronunciation for Computer-Assisted Pronunciation Training
4. An Improved Goodness of Pronunciation (GoP) Measure for Pronunciation Evaluation with DNN-HMM System Considering HMM Transition Probabilities
5. Mispronunciation Detection Using Deep Convolutional Neural Network Features and Transfer Learning-Based Model for Arabic Phonemes
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1. Automatic Accent Identification Using Less Data: a Shift from Global to Segmental Accent;Arabian Journal for Science and Engineering;2024-08-13
2. Automatic Pronunciation Assessment Systems for English Students from Argentina;Communications of the ACM;2024-08
3. Deep transfer learning for automatic speech recognition: Towards better generalization;Knowledge-Based Systems;2023-10
4. Relative Dynamic Time Warping Comparison for Pronunciation Errors;ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2023-06-04
5. Multiple ensemble learning methods for Mandarin multisyllabic pronunciation assessment;2023 IEEE International Conference on Control, Electronics and Computer Technology (ICCECT);2023-04-28
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