Search Results for author:
Found 2 papers, 0 papers with code
Phonetic and Prosody-aware Self-supervised Learning Approach for Non-native Fluency Scoring
Specifically, we first pre-train the model using a reconstruction loss function, by masking phones and their durations jointly on a large amount of unlabeled speech and text prompts.
Improving Non-native Word-level Pronunciation Scoring with Phone-level Mixup Data Augmentation and Multi-source Information
Moreover, we utilize multi-source information (e. g., MFCC and deep features) to further improve the scoring system performance.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
