Showing 5 open source projects for "assembly operating system"

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  • 1
    whisper.cpp

    whisper.cpp

    Port of OpenAI's Whisper model in C/C++

    whisper.cpp is a lightweight, C/C++ reimplementation of OpenAI’s Whisper automatic speech recognition (ASR) model—designed for efficient, standalone transcription without external dependencies. The entire high-level implementation of the model is contained in whisper.h and whisper.cpp. The rest of the code is part of the ggml machine learning library. The command downloads the base.en model converted to custom ggml format and runs the inference on all .wav samples in the folder samples....
    Downloads: 443 This Week
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  • 2
    Vosk Speech Recognition Toolkit

    Vosk Speech Recognition Toolkit

    Offline speech recognition API for Android, iOS, Raspberry Pi

    Vosk is an offline open source speech recognition toolkit. It enables speech recognition for 20+ languages and dialects - English, Indian English, German, French, Spanish, Portuguese, Chinese, Russian, Turkish, Vietnamese, Italian, Dutch, Catalan, Arabic, Greek, Farsi, Filipino, Ukrainian, Kazakh, Swedish, Japanese, Esperanto, Hindi, Czech, Polish. More to come. Vosk models are small (50 Mb) but provide continuous large vocabulary transcription, zero-latency response with streaming API,...
    Downloads: 105 This Week
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  • 3
    NASH OS

    NASH OS

    Nash Operating System for Modern Ecommerce

    The all-built-in-one, automatic, ready-to-go out-of-box, easy-to-use state-of-the-art, and really awesome NASH OS! Over 25,000+ flexible features and controls and all scalable!! The most powerful solution ever built to instantly deliver new heights of online ecommerce enterprise to you.
    Downloads: 0 This Week
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  • 4
    Perlbox Voice is an voice enabled application to bring your desktop under your command. With a single word, you can start your web browser, your favorite editor or whatever you want. This is the Linux and Unix voice recognition solution.
    Downloads: 0 This Week
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  • 5
    This project will show how to implement the Hidden Markov Model approximations of Voice Recognition into embedded and low power systems.
    Downloads: 0 This Week
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