Improving the Efficiency of Dysarthria Voice Conversion System Based on Data Augmentation-Reference-Cited by-同舟云学术

Improving the Efficiency of Dysarthria Voice Conversion System Based on Data Augmentation

Published:2023 Issue: Volume:31 Page:4613-4623
ISSN:1534-4320
Container-title:IEEE Transactions on Neural Systems and Rehabilitation Engineering
language:
Short-container-title:IEEE Trans. Neural Syst. Rehabil. Eng.

Author:

Zheng Wei-Zhong¹^ORCID,Han Ji-Yan¹^ORCID,Chen Chen-Yu¹,Chang Yuh-Jer¹,Lai Ying-Hui²^ORCID

Affiliation:

1. Department of Biomedical Engineering, National Yang Ming Chiao Tung University, Taipei, Taiwan

2. Department of Biomedical Engineering and the Medical Device Innovation & Translation Center, National Yang Ming Chiao Tung University, Taipei, Taiwan

Funder

Ministry of Science and Technology, Taiwan

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Biomedical Engineering,General Neuroscience,Internal Medicine,Rehabilitation

Link

http://xplorestaging.ieee.org/ielx7/7333/10031624/10313325.pdf?arnumber=10313325

Reference38 articles.

1. A speech enhancement approach using piecewise linear approximation of an explicit model of environmental distortions

2. Development of the Mandarin Hearing in Noise Test (MHINT)

3. A joint-feature learning-based voice conversion system for dysarthric user based on deep learning technology

4. Voice conversion using deep Bidirectional Long Short-Term Memory based Recurrent Neural Networks

5. Improving Dysarthric Speech Intelligibility using Cycle-consistent Adversarial Training

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1. One-Shot Voice Conversion Based on Style Generative Adversarial Networks with ESR and DSNet;Circuits, Systems, and Signal Processing;2024-04-21

2. Using StarGANv2 Voice Conversion to Enhance the Quality of Dysarthric Speech;2024 International Conference on Artificial Intelligence in Information and Communication (ICAIIC);2024-02-19