Showing 4 open source projects for "speech decoder"

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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. ...
    Downloads: 10 This Week
    Last Update:
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  • 2
    FireRedASR

    FireRedASR

    Open-source industrial-grade ASR models

    FireRedASR is an industrial-grade family of open-source automatic speech recognition models designed to provide high-precision speech-to-text performance across languages including Mandarin, English, and various Chinese dialects, achieving new state-of-the-art benchmarks on public test sets. The project includes multiple model variants to meet different application needs, such as high-accuracy end-to-end interaction using an encoder-adapter-LLM framework and efficient real-time recognition using attention-based encoder-decoder architectures, giving developers flexibility in balancing performance and resource constraints. ...
    Downloads: 1 This Week
    Last Update:
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  • 3
    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.
    Downloads: 4 This Week
    Last Update:
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  • 4
    Denoiser

    Denoiser

    Real Time Speech Enhancement in the Waveform Domain (Interspeech 2020)

    Denoiser is a real-time speech enhancement model operating directly on raw waveforms, designed to clean noisy audio while running efficiently on CPU. It uses a causal encoder-decoder architecture with skip connections, optimized with losses defined both in the time domain and frequency domain to better suppress noise while preserving speech. Unlike models that operate on spectrograms alone, this design enables lower latency and coherent waveform output.
    Downloads: 4 This Week
    Last Update:
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