Showing 11 open source projects for "high performance computing"

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  • 1
    OmniVoice

    OmniVoice

    High-Quality Voice Cloning TTS for 600+ Languages

    The OmniVoice project is a cutting-edge multilingual text-to-speech system designed to generate high-quality speech across more than 600 languages. Built on a diffusion language model-style architecture, it combines scalability with strong performance, enabling both natural-sounding voice synthesis and efficient inference speeds. One of its most notable capabilities is zero-shot voice cloning, allowing users to replicate a speaker’s voice using only a short reference audio clip. ...
    Downloads: 41 This Week
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  • 2
    VoxCPM2

    VoxCPM2

    Tokenizer-Free TTS for Multilingual Speech Generation

    VoxCPM2 is an advanced open-source text-to-speech system that redefines speech synthesis by eliminating traditional tokenization and instead generating continuous speech representations through a diffusion-based autoregressive architecture. Built on top of the MiniCPM model family, it enables highly natural, expressive, and context-aware speech generation that adapts tone, emotion, and pacing directly from input text. The system is trained on massive multilingual datasets, enabling support...
    Downloads: 25 This Week
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  • 3
    Miso TTS

    Miso TTS

    Miso TTS is an 8 billion, highly emotive text-to-speech model

    ...With its focus on emotive speech generation, Miso TTS delivers state-of-the-art performance for AI voice applications, virtual assistants, and conversational AI experiences.
    Downloads: 1 This Week
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  • 4
    Qwen3-TTS

    Qwen3-TTS

    Qwen3-TTS is an open-source series of TTS models

    Qwen3-TTS is an open-source text-to-speech (TTS) project built around the Qwen3 large language model family, focused on generating high-quality, natural-sounding speech from plain text input. It provides researchers and developers with tools to transform text into expressive, intelligible audio, supporting multiple languages and voice characteristics tuned for clarity and fluidity. The project includes pre-trained models and inference scripts that let users synthesize speech locally or...
    Downloads: 17 This Week
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  • 5
    Matcha-TTS

    Matcha-TTS

    A fast TTS architecture with conditional flow matching

    ...Users can train on standard datasets like LJSpeech or plug in their own corpora, with helper tools for computing dataset statistics, extracting phoneme durations, and running multi-GPU training.
    Downloads: 7 This Week
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  • 6
    WhisperSpeech

    WhisperSpeech

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

    ...Its architecture follows a token-based, multi-stage pipeline inspired by AudioLM and SPEAR-TTS: Whisper is used to produce semantic tokens, EnCodec compresses the waveform into acoustic tokens, and Vocos reconstructs high-fidelity audio from those tokens. The repository includes notebooks and scripts for inference, long-form synthesis, and finetuning, as well as pre-trained models and converted datasets hosted on Hugging Face. Performance optimizations like torch.compile, KV-caching, and architectural tweaks allow the main model to reach up to 12× real-time speed on a consumer RTX 4090.
    Downloads: 1 This Week
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  • 7
    MLX-Audio

    MLX-Audio

    A text-to-speech, speech-to-text and speech-to-speech library

    MLX-Audio is a speech library built on Apple’s MLX framework and optimized for Apple Silicon machines (M-series Macs). It focuses on text-to-speech and speech-to-speech workflows, with APIs and a command-line interface that make it easy to generate high-quality audio from text. Because it uses MLX and targets Apple Silicon, inference is fast and can take advantage of hardware acceleration and quantization for efficient on-device performance. The project provides a straightforward CLI (mlx_audio.tts.generate) as well as a Python API for programmatic generation of audio, including parameters for voice choice, speed, language hints, output format, and sample rate. ...
    Downloads: 7 This Week
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  • 8
    Audiblez

    Audiblez

    Generate audiobooks from e-books

    Audiblez is a tool for generating high-quality .m4b audiobooks directly from .epub e-books using the Kokoro-82M neural text-to-speech model. It focuses on making audiobook creation easy and fast: from a single command, the tool splits an e-book into chapters, synthesizes audio for each section, and then merges the results into a structured audiobook with chapter-based WAV files and a final .m4b container. The Kokoro-82M model it uses is compact (82M parameters) yet natural sounding, trained...
    Downloads: 6 This Week
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  • 9
    CSM (Conversational Speech Model)

    CSM (Conversational Speech Model)

    A Conversational Speech Generation Model

    The CSM (Conversational Speech Model) is a speech generation model developed by Sesame AI that creates RVQ audio codes from text and audio inputs. It uses a Llama backbone and a smaller audio decoder to produce audio codes for realistic speech synthesis. The model has been fine-tuned for interactive voice demos and is hosted on platforms like Hugging Face for testing. CSM offers a flexible setup and is compatible with CUDA-enabled GPUs for efficient execution.
    Downloads: 4 This Week
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  • 10
    TTS

    TTS

    Deep learning for text to speech

    TTS is a library for advanced Text-to-Speech generation. It's built on the latest research, was designed to achieve the best trade-off among ease-of-training, speed, and quality. TTS comes with pre-trained models, tools for measuring dataset quality, and is already used in 20+ languages for products and research projects. Released models in PyTorch, Tensorflow and TFLite. Tools to curate Text2Speech datasets underdataset_analysis. Demo server for model testing. Notebooks for extensive model...
    Downloads: 1 This Week
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  • 11
    Dia-1.6B

    Dia-1.6B

    Dia-1.6B generates lifelike English dialogue and vocal expressions

    Dia-1.6B is a 1.6 billion parameter text-to-speech model by Nari Labs that generates high-fidelity dialogue directly from transcripts. 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.
    Downloads: 0 This Week
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