Showing 4 open source projects for "data integration"

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    MusicFreePlugins

    MusicFreePlugins

    MusicFreePlayPlugin

    The MusicFreePluginsc project is a collection and framework for plugins that extend the functionality of the MusicFree ecosystem by providing access to various music sources and features. It defines a standardized interface for plugin development, allowing contributors to implement features such as search, playback, and metadata retrieval. The system is designed to be modular, enabling users to install, update, and manage plugins independently of the core application. It supports multiple...
    Downloads: 1 This Week
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  • 2
    MusicFreeDesktop

    MusicFreeDesktop

    Plug-in, customized, ad-free free music player

    The MusicFreeDesktop project is a desktop version of the MusicFree ecosystem, providing a plugin-driven music player for Windows, macOS, and Linux environments. It retains the same philosophy as its mobile counterpart, acting as a core player while delegating content sourcing and advanced features to external plugins. The application is built using modern web technologies and offers a customizable interface with support for themes and layout adjustments. It enables users to search, stream,...
    Downloads: 3 This Week
    Last Update:
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  • 3
    cdrtfe

    cdrtfe

    Burn optical discs in various formats

    cdrtfe is a CD/DVD/BD burning application for Microsoft Windows. You can burn data discs, Audio CDs, XCDs, (S)VCDs and DVD-Video discs. It supports creation and writing of ISO images and bootable discs. cdrtfe has a multi-language interface and is also available as portable version.
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    Downloads: 443 This Week
    Last Update:
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  • 4
    EnCodec

    EnCodec

    State-of-the-art deep learning based audio codec

    Encodec is a neural audio codec developed by Meta for high-fidelity, low-bitrate audio compression using end-to-end deep learning. Unlike traditional codecs (like MP3 or Opus), Encodec uses a learned quantizer and decoder to reconstruct complex waveforms with remarkable accuracy at bitrates as low as 1.5 kbps. It employs a convolutional encoder–decoder architecture trained with perceptual loss functions that optimize for human auditory quality rather than raw waveform distance. The model can...
    Downloads: 1 This Week
    Last Update:
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