An Adaptive-Learning-Based Generative Adversarial Network for One-to-One Voice Conversion
Author:
Affiliation:
1. Department of Computer Science and Engineering, National Institute of Technology Durgapur, Durgapur, India
2. Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, India
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Science Applications,Artificial Intelligence
Link
http://xplorestaging.ieee.org/ielx7/9078688/10023979/09709124.pdf?arnumber=9709124
Reference51 articles.
1. Voice Conversion Using a Perceptual Criterion
2. SEGAN: Speech Enhancement Generative Adversarial Network
3. Deep speech enhancement for reverberated and noisy signals using wide residual networks;gonzález,2019
4. WaveCRN: An Efficient Convolutional Recurrent Neural Network for End-to-End Speech Enhancement
5. Deep Residual Learning for Image Recognition
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