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OpenAI's open-source general-purpose speech recognition model. The whisper command transcribes many languages, translates foreign speech into English and writes subtitle files. Needs FFmpeg; faster with a GPU.

C/C++ port of OpenAI's Whisper speech recognition model that transcribes audio offline and outputs subtitles. Runs on CPU, with Apple Silicon and various GPU acceleration. Download a ggml-format model first.

Fast speech transcription built on faster-whisper, with word-level timestamps and speaker diarization, suited to meeting notes and subtitles. Diarization needs a Hugging Face token; GPU acceleration needs CUDA.

Offline speech transcription and translation based on Whisper; audio never leaves your machine. buzz add exports lectures, interviews and meeting recordings to TXT, SRT or VTT. pip install needs Python 3.12 and FFmpeg; a desktop app is also available. Check transcripts manually.

All-in-one video translation and dubbing: chains speech recognition, subtitle translation, multi-speaker AI voiceover and audio-video muxing, with local or online models like Faster-Whisper, DeepSeek and Edge-TTS. cli.py supports headless batch runs. Needs FFmpeg.

CLI version of the VideoCaptioner subtitle assistant: transcribes courses, lectures and interviews, uses an LLM to segment, proofread and translate, then burns subtitles into the video. Free ASR and Bing translation work out of the box; LLM refinement needs an API key. Python 3.10 to 3.12.

Adds voice conversations to Claude Code and other agents: speak, and it detects silence, transcribes, and reads replies aloud. Runs offline with local Whisper and Kokoro, or uses OpenAI's speech APIs; needs a microphone and speakers.

Lets Claude Code watch videos: extracts frames with ffmpeg and transcribes timestamped audio from local files or YouTube links, to review footage, summarize lectures or find on-screen text. Needs Node.js 20+ and ffmpeg (yt-dlp for YouTube); transcribe with local Whisper or a Gemini/OpenAI key.

Local transcription that's compatible with the OpenAI Whisper CLI but faster and lighter: outputs SRT/VTT subtitles or text and can transcribe a live microphone. Needs Python; models download on first run; speaker labels need pyannote.audio and a Hugging Face token.

Automatically aligns subtitles to audio and video with a neural network, and can transcribe subtitles with Whisper or translate them with local models; supports 10+ formats such as SRT, TTML and SCC. Needs Python 3.9-3.12 and FFmpeg; transcription and translation need the llm extra.