Showing 6 open source projects for "voice cloning"

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  • 1
    IndexTTS2

    IndexTTS2

    Industrial-level controllable zero-shot text-to-speech system

    IndexTTS is a modern, zero-shot text-to-speech (TTS) system engineered to deliver high-quality, natural-sounding speech synthesis with few requirements and strong voice-cloning capabilities. It builds on state-of-the-art models such as XTTS and other modern neural TTS backbones, improving them with a conformer-based speech conditional encoder and upgrading the decoder to a high-quality vocoder (BigVGAN2), leading to clearer and more natural audio output. The system supports zero-shot voice cloning — meaning it can mimic a target speaker’s voice from a short reference sample — making it versatile for multi-voice uses. ...
    Downloads: 8 This Week
    Last Update:
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  • 2
    Step-Audio

    Step-Audio

    Open-source framework for intelligent speech interaction

    ...The design moves beyond traditional separate-component pipelines (ASR → text model → TTS), instead offering a multimodal model that ingests speech or audio and produces speech accordingly, enabling natural dialogue, voice cloning, and expressive speech synthesis. Through its architecture, Step-Audio supports multilingual interaction, dialects, emotional tones (joy, sadness, etc.), and even more creative speech styles (like rap or singing), while allowing dynamic control over speech characteristics. It also provides a “generative data engine,” which can produce synthetic speech data (cloning voices, varying style) to support TTS training.
    Downloads: 0 This Week
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  • 3
    GLM-TTS

    GLM-TTS

    Controllable & emotion-expressive zero-shot TTS

    GLM-TTS is an advanced text-to-speech synthesis system built on large language model technologies that focuses on producing high-quality, expressive, and controllable spoken output, including features like emotion modulation and zero-shot voice cloning. It uses a two-stage architecture where a generative LLM first converts text into intermediate speech token sequences and then a Flow-based neural model converts those tokens into natural audio waveforms, enabling rich prosody and voice character even for unseen speakers. The system introduces a multi-reward reinforcement learning framework that jointly optimizes for voice similarity, emotional expressiveness, pronunciation, and intelligibility, yielding output that can rival commercial options in naturalness and expressiveness. ...
    Downloads: 0 This Week
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  • 4
    MiniCPM-o

    MiniCPM-o

    A GPT-4o Level MLLM for Vision, Speech and Multimodal Live Streaming

    ...With 8 billion parameters, MiniCPM-o 2.6 surpasses its predecessors in versatility and efficiency, making it one of the most robust models available. It supports both text and audio inputs to generate outputs in various forms, including voice cloning, emotion control, and interactive role-playing.
    Downloads: 0 This Week
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  • 5
    FireRedTTS-2

    FireRedTTS-2

    Long-form streaming TTS system for multi-speaker dialogue generation

    ...It features a specialized streaming speech tokenizer and a dual-transformer architecture that enables low latency and high-quality synthesis, making it suitable for interactive systems like chatbots, podcasts, and applications where dynamic turn-taking between speakers is essential. FireRedTTS2 supports multilingual output and speaker flexibility, enabling scenarios that involve language switching, cross-lingual voice cloning, and expressive dialogue generation that maintains consistency over longer utterances.
    Downloads: 0 This Week
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  • 6
    Dia-1.6B

    Dia-1.6B

    Dia-1.6B generates lifelike English dialogue and vocal expressions

    ...Designed for realistic vocal performance, Dia supports expressive features like emotion, tone control, and non-verbal cues such as laughter, coughing, or sighs. The model accepts speaker conditioning through audio prompts, allowing limited voice cloning and speaker consistency across generations. It is optimized for English and built for real-time performance on enterprise GPUs, though CPU and quantized versions are planned. The format supports [S1]/[S2] tags to differentiate speakers and integrates easily into Python workflows. While not tuned to a specific voice, user-provided audio can guide output style. ...
    Downloads: 0 This Week
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