Showing 4 open source projects for "export"

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    Matcha-TTS

    Matcha-TTS

    A fast TTS architecture with conditional flow matching

    Matcha-TTS is a non-autoregressive neural text-to-speech architecture that uses conditional flow matching to generate speech quickly while maintaining natural quality. It models speech as an ODE-based generative process, and conditional flow matching lets it reach high-quality audio in only a few synthesis steps, which greatly reduces latency compared to score-matching diffusion approaches. The model is fully probabilistic, so it can generate diverse realizations of the same text while still...
    Downloads: 1 This Week
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  • 2
    ESPnet

    ESPnet

    End-to-end speech processing toolkit

    ESPnet is a comprehensive end-to-end speech processing toolkit covering a wide spectrum of tasks, including automatic speech recognition (ASR), text-to-speech (TTS), speech translation (ST), speech enhancement, speaker diarization, and spoken language understanding. It uses PyTorch as its deep learning engine and adopts a Kaldi-style data processing pipeline for features, data formats, and experimental recipes. This combination allows researchers to leverage modern neural architectures while...
    Downloads: 0 This Week
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  • 3
    Bert-VITS2

    Bert-VITS2

    VITS2 backbone with multilingual-bert

    ...It provides emotional modeling through “emo embeddings,” allowing voices to be conditioned on different affective states during synthesis. Releases include optimizations for Japanese and English alignment, expanded training data, spec caching and pre-generation tools, as well as ONNX export for more lightweight inference deployments.
    Downloads: 1 This Week
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  • 4
    WaveRNN

    WaveRNN

    WaveRNN Vocoder + TTS

    ...A quick_start.py script allows users to immediately synthesize example sentences from a pretrained model and inspect both generated audio and attention plots. For custom TTS, the project guides you through training Tacotron, forcing GTA spectrogram export when desired, training WaveRNN with or without GTA, and then running joint generation.
    Downloads: 0 This Week
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