Wenet Automatic #Speech#Recognition toolkit. https://github.com/wenet-e2e/wenet https://wenet.org.cn/wenet/
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🚨 GitHub 监控消息提醒 🚨发现关键词:#漏洞#验证#检测#分析 📦项目名称:LLM-MultiAgent-StackOverflow-Detector 👤项目作者:uguj 🛠开发语言: Python ⭐Star数量: 0 | 🍴Fork数量: 0 📅更新时间: 2026-05-18 10:51:12 📝项目描述: 基于ReAct范式的多智能体栈缓冲区溢出检测框架,用于C/C++代码漏洞分析。 - Finder Agent:基于libclang的AST解析,识别危险函数调用 - Tracer Agent:语法树回溯,分析参数可控性 - Hypothesis Agent:调用Qwen2.5-Coder大语言模型生成智能漏洞假设 - Verifier Agent:通过angr符号执行与objdump静态匹配进行二进制验证 框架形成“发现→追踪→假设→验证→反馈”的闭环检测流程。 本仓库包含毕业设计《基于大语言模型的栈溢出漏洞检测研究》的全部源代码、测试用例及实验结果。 🔗点击访问项目地址
搜索 #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 · 2017/09/18 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