Libreware
@libreware · Post #1085 · 05/04/2022, 09:32 AM
Wenet Automatic #Speech#Recognition toolkit. https://github.com/wenet-e2e/wenet https://wenet.org.cn/wenet/
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Source channel @githubtrending · Post #14877 · Jun 28
#python#bounty#bugbounty#bypass#cheatsheet#enumeration#hacking#hacktoberfest#methodology#payload#payloads#penetration_testing#pentest#privilege_escalation#redteam#security#vulnerability#web_application Payloads All The Things is a comprehensive collection of useful payloads and bypass techniques for web application security testing and penetration testing. It offers detailed documentation for each vulnerability, including how to exploit it and ready-to-use payloads, plus files for tools like Burp Intruder. You can contribute your own payloads or improvements, making it a collaborative resource. It also links to related projects for internal network and hardware pentesting, and provides learning resources like books and videos. Using this resource helps you efficiently find and test security weaknesses in web applications, improving your pentesting effectiveness and knowledge. https://github.com/swisskyrepo/PayloadsAllTheThings
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Libreware
@libreware · Post #1084 · 05/04/2022, 09:32 AM
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 · 01/09/2022, 02:56 PM
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 · 10/06/2023, 11:18 AM
#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 · 09/18/2017, 11:30 AM
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 · 03/09/2023, 10:58 PM
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