Showing 3 open source projects for "gaussian mixture model"

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  • 1
    DeepEP

    DeepEP

    DeepEP: an efficient expert-parallel communication library

    ...The library also supports low-precision operations (such as FP8) to reduce memory and bandwidth usage during communication. DeepEP is aimed at large-scale model inference or training systems where expert parallelism is used to scale model capacity without replicating entire networks.
    Downloads: 0 This Week
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  • 2
    SVoice (Speech Voice Separation)

    SVoice (Speech Voice Separation)

    We provide a PyTorch implementation of the paper Voice Separation

    ...This project presents a deep learning framework capable of separating mixed audio sequences where several people speak simultaneously, without prior knowledge of how many speakers are present. The model employs gated neural networks with recurrent processing blocks that disentangle voices over multiple computational steps, while maintaining speaker consistency across output channels. Separate models are trained for different speaker counts, and the largest-capacity model dynamically determines the actual number of speakers in a mixture. ...
    Downloads: 2 This Week
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  • 3
    This project hosts tools used for analysis of Gaussian Mixture Distributions (GMDs) which are used for statistical signal processing. The tools are libraries for implementing GMD operations and programs used to analyze properties of GMDs.
    Downloads: 0 This Week
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