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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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djangoproject

@djangoproject · Post #240 · 01/25/2017, 10:03 AM

http://www.aparat.com/v/4nbc9 This talk gives a quick overview of Python's capabilities as a #data_processing and #machine_learning tool through practical examples: gathering data from the web or a local file, validating/modifying it and finally analyzing it to build models for #classification and #prediction#tasks.