Showing 4 open source projects for "model driven"

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  • 1
    DramaBox

    DramaBox

    super expressive prompting model based on ltx2.3

    DramaBox is an expressive text-to-speech and voice cloning project from Resemble AI built on top of the LTX-2.3 audio branch. It generates speech from prompts that control not only the spoken text, but also speaker identity, emotion, delivery style, laughs, sighs, pauses, and transitions. Users can optionally provide a voice reference of around 10 seconds or more to clone the target timbre while still guiding performance through scene-style prompting. The project includes a warm inference...
    Downloads: 5 This Week
    Last Update:
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  • 2
    WhisperSpeech

    WhisperSpeech

    An Open Source text-to-speech system built by inverting Whisper

    WhisperSpeech is an open-source text-to-speech system created by “inverting” OpenAI’s Whisper, reusing its strengths as a semantic audio model to generate speech instead of only transcribing it. The project aims to be for speech what Stable Diffusion is for images: powerful, hackable, and safe for commercial use, with code under Apache-2.0/MIT and models trained only on properly licensed data. Its architecture follows a token-based, multi-stage pipeline inspired by AudioLM and SPEAR-TTS:...
    Downloads: 2 This Week
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  • 3
    Luna AI

    Luna AI

    Virtual AI anchor that combines state-of-the-art technology

    Luna AI is a virtual AI streamer framework designed to power an interactive VTuber that can go live on major platforms and chat with viewers in real time. It is built around a core assistant persona called “Luna AI,” which can be driven by a wide range of large language models and platforms, including GPT-style APIs, Claude, LangChain-based backends, ChatGLM, Kimi, Ollama, and many others. The project supports multiple rendering backends for the avatar, such as Live2D, Unreal Engine (UE),...
    Downloads: 2 This Week
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  • 4
    OpenSeq2Seq

    OpenSeq2Seq

    Toolkit for efficient experimentation with Speech Recognition

    ...It supports multi-GPU and multi-node data-parallel training, and integrates with Horovod to scale out across large GPU clusters. Mixed-precision support (float16) is optimized for NVIDIA Volta and Turing GPUs, allowing significant speedups and memory savings without sacrificing model quality. The project comes with configuration-driven training scripts, documentation, and examples that demonstrate how to set up pipelines for tasks.
    Downloads: 0 This Week
    Last Update:
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