Showing 4 open source projects for "text browser"

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  • 1
    WhisperLive

    WhisperLive

    A nearly-live implementation of OpenAI's Whisper

    WhisperLive is a “nearly live” implementation of OpenAI’s Whisper model focused on real-time transcription. It runs as a server–client system in which the server hosts a Whisper backend and clients stream audio to be transcribed with very low delay. The project supports multiple inference backends, including Faster-Whisper, NVIDIA TensorRT, and OpenVINO, allowing you to target GPUs and different CPU architectures efficiently. It can handle microphone input, pre-recorded audio files, and...
    Downloads: 12 This Week
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  • 2
    Speech-AI-Forge

    Speech-AI-Forge

    Speech-AI-Forge is a project developed around TTS generation model

    Speech-AI-Forge is a full-stack project built around modern text-to-speech generation models, providing both an API server and a Gradio-based web UI for interactive use. At its core, it acts as a hub that wires together multiple speech-related capabilities, including TTS, speech-to-text and LLM-based control flows, behind a consistent interface. The system is designed to be deployed in several ways: you can try it online via hosted demos, spin it up in a one-click Colab environment, run it...
    Downloads: 4 This Week
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  • 3
    clone-voice

    clone-voice

    A sound cloning tool with a web interface, using your voice

    Clone-voice is a local voice-cloning tool that lets you synthesize speech in any target voice or convert one recording into another voice using the same timbre. It is built around Coqui’s XTTS-v2 model, so it inherits multilingual support and modern neural TTS quality while wrapping it in a user-friendly desktop workflow. The app is designed to be very easy to use: you download a precompiled package, double-click app.exe, and it launches a browser-based web interface where you control...
    Downloads: 7 This Week
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  • 4
    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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