Libreware
@libreware · Post #1085 · 04.05.2022 г., 09:32
Wenet Automatic #Speech#Recognition toolkit. https://github.com/wenet-e2e/wenet https://wenet.org.cn/wenet/
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Изходен канал @clockstackwheels · Post #93 · 26.10
Телеграм запустил рекламную платформу, которую многие ждали. В том числе я, потому что неофициальные средства продвижения здесь хоть и существуют, вызывают у меня стойкое неприятие. Реклама будет отображаться в каналах, в которых больше 1000 подписчиков (вам, как моим читателям, можно пока не переживать). Внешние ссылки запрещены. Есть, однако, маленький нюанс. Минимальный бюджет рекламной кампании: 2 миллиона евро. С одной стороны, это хорошо, потому что не будет бесконечной инфоцыганщины, которой переполнен, например, ВКонтакте. С другой стороны, 90% рекламного рынка так и останется в чёрной зоне, то есть почти ни для кого ничего не поменяется, кроме Дурова. Такая себе забота о пользователях. Понравилось вот это: Sponsored Messages are currently in test mode. Once they are fully launched and allow Telegram to cover its basic costs, we will start sharing ad revenue with the owners of public channels in which sponsored messages are displayed Переводится так: мы будем забирать все деньги себе и не делиться с авторами каналов, пока не посчитаем, что забрали себе достаточно. #web
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Libreware
@libreware · Post #1084 · 04.05.2022 г., 09:32
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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Libreware
@libreware · Post #1021 · 09.01.2022 г., 14:56
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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Libreware
@libreware · Post #1192 · 06.10.2023 г., 11:18
#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
@djangoproject · Post #448 · 18.09.2017 г., 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.
Libreware
@libreware · Post #1114 · 09.03.2023 г., 22:58
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