Wenet Automatic #Speech#Recognition toolkit. https://github.com/wenet-e2e/wenet https://wenet.org.cn/wenet/
Hashtags
TGTGInsighttelegram intelligenceLIVE / telegram public index
🥳Bugun Telegram 10 yoshga to'ldi. Pavel Durovtug'ilgan kun haqida shunday dedi: Atigi oʻn yil ichida Telegram 800 milliondan ortiq faol foydalanuvchilarga ega boʻldi. Yillar davomida ko'plab yangilanishlar va takomillashtirishlar orqali Telegram zamonaviy xabar almashish tajribasi qanday bo'lishi kerakligini qayta belgilab berdi. Telegram uchun navbatdagi qadam - bu xabar almashishdan tashqariga chiqish va umuman, ijtimoiy tarmoqlarda innovatsiyalarni rivojlantirish. Biz mashhurligimizdan milliardlab odamlarning hayotini yaxshi tomonga o'zgartirish, sayyoramizdagi odamlarni ilhomlantirish va ko'tarish uchun foydalanishimiz kerak. Bugungi kunda barcha foydalanuvchilar uchun hikoyalarning bosqichma-bosqich chiqarilishi Telegram tarixidagi ushbu yangi bosqichning boshlanishini anglatadi. O'tgan o'n yillik hayajonli bo'lsa-da, keyingi 10 yil Telegram o'zining haqiqiy salohiyatiga erishadigan vaqt bo'ladi. 🥳 #durov#telegram#10yosh ✅@TGraphUz | 📺YouTube
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검색: #recognition
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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
@djangoproject · Post #448 · 2017. 09. 18. AM 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