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Source channel @githubtrending · Post #15495 · Feb 15

#c_lang Moonshine Voice is an open-source toolkit for fast, private on-device speech-to-text that beats Whisper's accuracy and speed (up to 5x faster, 6.65% vs. 7.44% WER) with tiny 26MB-245M models for live apps on phones, Raspberry Pi, and more. It streams results as you speak, supports English/Spanish/Mandarin/etc., and handles transcription/commands easily via simple APIs on Python/iOS/Android. You benefit by building responsive voice apps offline without accounts, keys, or cloud costs—perfect for real-time tools like translators or assistants. https://github.com/moonshine-ai/moonshine

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@githubtrending · Post #15271 · 11/05/2025, 12:30 PM

#cplusplus#arm#baidu#deep_learning#embedded#fpga#mali#mdl#mobile#mobile_deep_learning#neural_network Paddle Lite is a lightweight, high-performance deep learning inference framework designed to run AI models efficiently on mobile, embedded, and edge devices. It supports multiple platforms like Android, iOS, Linux, Windows, and macOS, and languages including C++, Java, and Python. You can easily convert models from other frameworks to PaddlePaddle format, optimize them for faster and smaller deployment, and run them with ready-made examples. This helps you deploy AI applications quickly on various devices with low memory use and fast speed, making it ideal for real-time, resource-limited environments. It also supports many hardware accelerators for better performance. https://github.com/PaddlePaddle/Paddle-Lite