Wenet Automatic #Speech#Recognition toolkit. https://github.com/wenet-e2e/wenet https://wenet.org.cn/wenet/
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Источник @codev0s · Post #9 · 18 мая
Максим Эзьер написал большое руководство по работе с WebGL — "WebGL guide". В руководстве с азов объясняется создание интерактивной трёхмерной сцены без использования сторонних библиотек. Используется только чистый JS и WebGL. В самом начале есть раздел про математику, которая необходима для работы с графикой. Затем объясняется процесс создания простых двумерных и трёхмерных сцен с подробным объяснением примеров исходного кода. Есть пример текстурирования объектов и работы с источниками света. В конце статьи есть список наиболее распространённых ошибок. Про них полезно знать при отладке кода. В общем, если хотели потыкать WebGL, рекомендую заглянуть в это руководство. #webgl#tutorial https://xem.github.io/articles/webgl-guide.html
Поиск: #recognition
Wenet Automatic #Speech#Recognition toolkit. https://github.com/wenet-e2e/wenet https://wenet.org.cn/wenet/
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Vosk Speech Recognition Toolkit 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. More to come. Vosk models are small (50 Mb) but provide continuous large vocabulary transcription, zero-latency response with streaming API, reconfigurable vocabulary and speaker identification. Speech recognition bindings implemented for various programming languages like Python, Java, Node.JS, C#, C++ and others. Vosk supplies speech recognition for chatbots, smart home appliances, virtual assistants. It can also create subtitles for movies, transcription for lectures and interviews. Vosk scales from small devices like Raspberry Pi or Android smartphone to big clusters. https://t.me/speech_recognition https://alphacephei.com/vosk https://github.com/alphacep/vosk-api
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SongRec An open-source Shazam client for Linux, written in Rust. Features: • Recognize audio from an audio file. • Recognize audio from the microphone. • Usage from both GUI and command line. • Provide an history of the recognized songs. • Continuous song detection. • Ability to recognize songs from your speakers rather than your microphone. Download: https://github.com/marin-m/SongRec#installation https://github.com/marin-m/SongRec @foss_desktop #music#shazam#recognition
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#Linux Desktop application that provides live #captioning FUTO Fellowship program interview; linux captions software 👉 Live Captions github: https://github.com/abb128/LiveCaptions 🔵 Q&A w/ billionaire alt-tech investor/philanthropist Eron Wolf https://www.youtube.com/watch?v=OJPmbcU-Vzo 🔵 FUTO Fellows program: https://futo.org/fellows/ 🔵 FUTO Youtube channel - @futotech ⚠️ Google's breaches of privacy have gone TOO FAR! https://www.youtube.com/watch?v=_vWAF13KigI #speech#recognition#stt#voice
@djangoproject · Post #448 · 18.09.2017, 11:30
https://medium.com/@GalarnykMichael/logistic-regression-using-python-sklearn-numpy-mnist-handwriting-recognition-matplotlib-a6b31e2b166a Logistic Regression using Python (#Sklearn, #NumPy, #MNIST, Handwriting #Recognition, #Matplotlib) #machine_learning.
https://writeout.ai #Transcribe and #translate any #audio file. 100% free to use. This website with source code available (it can be hosted locally) allows you to upload any audio file and receive a transcription and/or text translation. It uses OpenAI's Whisper API on the back end. Source on GitHub: https://github.com/beyondcode/writeout.ai #writeout#ai#speech#recognition