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Record and transcribe Teams, Zoom, and Google Meet calls locally with AI-powered speaker identification. Open-source alternative to Evaer, Otter.ai, and Fireflies. Offline speech-to-text using Whisper — no cloud, no subscriptions.
An advanced study tool that transforms raw audio recordings and PDF slides into structured, professional LaTeX university notes. Powered by fast local transcription (Whisper) and Google Gemini AI for intelligent summarization and context integration.
A lightweight, privacy-focused wrapper for Whisper.cpp on Android (via Termux). Features offline speech-to-text transcription with support for native Android file picking, batch processing, and subtitle generation.
A user-friendly desktop app to automatically generate accurate .srt subtitles for video or audio files. Powered by OpenAI's Whisper, it supports 99 languages and can also translate subtitles into English. It features a special mode for vertical videos (Reels, Shorts, TikTok) and can be run easily via desktop app or Docker.
🎵 Complete offline audio transcription system with speaker diarization using OpenAI Whisper and PyAnnote. Features automatic audio cleaning, precise timestamps, multiple output formats (JSON/TXT/Markdown), and support for 20+ audio formats. No external APIs required - works entirely offline.
"An offline video & audio transcription tool powered by OpenAI Whisper. Convert your tutorials, lectures, and podcasts into accurate text transcripts and use AI to generate summaries, notes, and mind maps — saving hours of time and boosting productivity."
Lightweight Windows screen recorder with built-in live transcription. Captures screen, mic, and system audio (Google Meet, Zoom). Produces an MP4 with embedded subtitles. Runs fully offline via faster-whisper.
Production-ready native Ruby batch inference for Cohere’s Arabic/English ASR model, with CPU/CUDA/Metal execution, Silero VAD, subtitles, and optional word-level timestamps.
Takarir is a lightweight, user-friendly macOS app that lets you generate subtitles from video files using advanced speech recognition — fast, offline, and privacy-friendly.
Privacy-first meeting transcription with speaker diarization. Records audio, transcribes with Whisper, and identifies speakers. All completely offline, no cloud, no data sharing.