Showing 4 open source projects for "aras-common"

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  • 1
    OpenVINO

    OpenVINO

    OpenVINO™ Toolkit repository

    OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference. Boost deep learning performance in computer vision, automatic speech recognition, natural language processing and other common tasks. Use models trained with popular frameworks like TensorFlow, PyTorch and more. Reduce resource demands and efficiently deploy on a range of Intel® platforms from edge to cloud. This open-source version includes several components: namely Model Optimizer, OpenVINO™ Runtime, Post-Training Optimization Tool, as well as CPU, GPU, MYRIAD, multi device and heterogeneous plugins to accelerate deep learning inferencing on Intel® CPUs and Intel® Processor Graphics. ...
    Downloads: 21 This Week
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  • 2
    VideoSrt

    VideoSrt

    Windows-GUI

    This is an open source Windows-GUI software tool that can recognize video speech and automatically generate subtitle SRT files. VideoSrtIt is written in Golanglanguage and developed based on lxn/walk Windows-GUI toolkit. Open source software tool that can recognize video speech and automatically generate subtitle SRT files. It is suitable for business scenarios that quickly and batch generate Chinese/English subtitles and text files for media (video/audio). Recognize video/audio speech to...
    Downloads: 25 This Week
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  • 3
    Tensorpack

    Tensorpack

    A Neural Net Training Interface on TensorFlow, with focus on speed

    ...Tensorpack squeezes the most performance out of pure Python with various auto parallelization strategies. There are too many symbolic function wrappers already. Tensorpack includes only a few common layers. You can use any TF symbolic functions inside Tensorpack.
    Downloads: 0 This Week
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  • 4

    Bavieca (www.bavieca.org)

    Bavieca is an open-source speech recognition tookit.

    Bavieca (www.bavieca.org) is an open-source speech recognition toolkit intended for speech research and as a platform for rapid development of speech-enabled solutions by non speech experts. It comprises the most common acoustic modeling and adaptation techniques including discriminative training, and efficient dynamic and FSM-based decoders that can operate in batch and live recognition modes. Bavieca is entirely written in C++ and distributed under the Apache 2.0 license. Bavieca was developed at Boulder Language Technologies (BLT) during the last three years in response to the needs of the research projects conducted within the company. ...
    Downloads: 0 This Week
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