Mongolian Pronunciation Data Enhancement Method Based on Separation Contrast Learning

• Published in: 2024 International Conference on Asian Language Processing (IALP) pp. 314 - 319
• Main Authors: Guo, Siyuan, Ma, Zhiqiang, Sun, Jiaqi, Qin, Yixiong
• Format: Conference Proceeding
• Language: English
• Published: IEEE 04.08.2024
• Subjects: Contrastive learning; data augmentation; data enhancement; Data models; Generators; Interference; Mongolian; Noise; Speech enhancement; Text-to-Speech; Vocoders

In the process of augmenting Mongolian speech data, the model overfits the noise data in the out-of-domain speech data set, causing the augmented speech data to be interfered by noise. This paper proposes a Mongolian Pronunciation Data Enhancement Method based on Separated Contrastive Learning (PEM-...