Abstract:
In this paper, we propose to use StarGAN, a pow-erful Generative Adversarial Network (GAN), to improve the quality of dysarthric speech. Through extensive experiments, we...Show MoreMetadata
Abstract:
In this paper, we propose to use StarGAN, a pow-erful Generative Adversarial Network (GAN), to improve the quality of dysarthric speech. Through extensive experiments, we demonstrate the effectiveness of StarGANv2-VC in converting dysarthric speech and significantly improving its intelligibility and naturalness. In addition, this research contributes to the field by conducting a comparative study between StarGANv2-VC and MaskCycleGAN-VC, another well-established GAN architecture, recently used in dysarthric speech conversion tasks. The results show that StarGANv2-VC performs the best, making it a promising solution for improving the speech quality of people suffering from dysarthria.
Published in: 2024 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)
Date of Conference: 19-22 February 2024
Date Added to IEEE Xplore: 20 March 2024
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