Improving CycleGAN-VC2 Voice Conversion by Learning MCD-Based Evaluation and Optimization
Author:
Affiliation:
1. Shahid Beheshti University,Faculty of Electrical Engineering,Tehran,Iran
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10334618/10334629/10334883.pdf?arnumber=10334883
Reference30 articles.
1. An Overview of Voice Conversion and Its Challenges: From Statistical Modeling to Deep Learning
2. Speaking-aid systems using GMM-based voice conversion for electrolaryngeal speech
3. Electrolaryngeal Speech Enhancement with Statistical Voice Conversion based on CLDNN
4. Parrotron: An End-to-End Speech-to-Speech Conversion Model and its Applications to Hearing-Impaired Speech and Speech Separation
5. Voice convergin: Speaker de-identification by voice transformation
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