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    StyleTTS 2

    StyleTTS 2

    Towards Human-Level Text-to-Speech through Style Diffusion

    StyleTTS2 is a state-of-the-art text-to-speech system that aims for human-level naturalness by combining style diffusion, adversarial training, and large speech language models. It extends the original StyleTTS idea by introducing a style diffusion model that can sample rich, realistic speaking styles conditioned on reference speech, allowing highly expressive and diverse prosody. The architecture uses a two-stage training process and leverages an auxiliary speech language model to guide generation toward more natural and coherent utterances. ...
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  • 2
    Bert-VITS2

    Bert-VITS2

    VITS2 backbone with multilingual-bert

    Bert-VITS2 is a neural text-to-speech project that combines a VITS2 backbone with a multilingual BERT front-end to produce high-quality speech in multiple languages. The core idea is to use BERT-style contextual embeddings for text encoding while relying on a refined VITS2 architecture for acoustic generation and vocoding. The repository includes everything needed to train, fine-tune, and run the model, from configuration files to preprocessing scripts, spectrogram utilities, and training entrypoints for multi-GPU and multi-node setups. ...
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