jaywalnut310/vits

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VITS: Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech Jaehyeon Kim, Jungil Kong, and Juhee Son In our recent paper, we propose VITS: Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech. Several recent end-to-end text-to-speech (TTS) models enabling single-stage training and parallel sampling have been proposed, but their sample quality does not match that of two-stage TTS systems. In this work, we present a parallel...