Tools

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.

Industrial-grade open-source speech recognition toolkit from Alibaba's ModelScope, with an agent-friendly funasr command that turns audio into text, JSON or SRT subtitles in one step, with speaker diarization and timestamps. Strong on Chinese. Requires PyTorch.

Unofficial Python library and CLI for driving Google NotebookLM (now Gemini Notebook): bulk-import sources, ask cited questions, and generate and download podcasts, videos, slides, quizzes and flashcards. Ships an agent skill. Relies on undocumented APIs and needs a Google sign-in.

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.

Open-source zero-shot TTS via f5-tts_infer-cli: from a few seconds of reference audio it reads Chinese or English text in the same voice, handy for lessons and videos. Needs Python, PyTorch and FFmpeg, ideally a GPU. Pretrained models are non-commercial; get consent before cloning a voice.

Offline speech toolkit for Apple Silicon Macs: CLI text-to-speech (including Chinese and voice cloning) and speech-to-text, for voicing lessons and explainer videos or transcribing lectures and interviews, with data staying local. Needs an M-series Mac and Python 3.10+; MP3 export needs ffmpeg.

Open-source alternative to NotebookLM's podcast feature: turns web pages, PDFs, images, YouTube videos or text into two-host conversational audio, useful for lecture notes or articles. Uses Gemini and OpenAI API keys by default, or local models plus free Edge TTS.

One command extracts or summarizes web pages, PDFs, YouTube videos, podcasts and media files, with JSON output. Summaries can use many model APIs, local models or a logged-in Codex or Claude CLI; plain extraction needs no key. Also has a browser sidebar extension.

Unofficial nlm CLI and MCP server for NotebookLM (now Gemini Notebook): bulk-create notebooks, import web pages and docs, and generate audio overviews, quizzes, flashcards, mind maps and slides for teaching and study. Relies on undocumented APIs and a Google sign-in, so it may break.

Unofficial CLI and MCP that let agents work with NotebookLM (now Gemini Notebook): bulk-import sources, ask questions with citations, and generate audio overviews, quizzes, flashcards, mind maps and slides. Uses undocumented APIs and may break; needs a Google sign-in and uv.

Gemini API development skills: gemini-api-dev (core API and SDKs), gemini-live-api-dev (real-time bidirectional audio/video streaming) and gemini-omni-flash-api (Omni video generation and editing), filling in APIs released after model training cutoffs. Maintained by Google's Gemini team.

MiniMax's official CLI, built for agents: chat with MiniMax models from the terminal and generate images, video and speech, plus speech transcription, image understanding and web search. Works with the international platform. Requires a MiniMax Token Plan subscription.

Translates a video's SRT subtitles into other languages and generates AI voice lines synced to the timings, producing translated subtitles and dubbed audio tracks. Needs Python, FFmpeg and Google Cloud, Azure, DeepL or ElevenLabs API keys; configure the ini files, then run python main.py.

Official skill for BaoCut, a subtitle app by Baoyu: transcribe audio and video, generate and translate subtitles, check speakers, adjust timing and export SRT or finished video. Needs BaoCut on an Apple silicon Mac (macOS 14+); on Windows the skill fetches a preview CLI.

Audio plugin suite: transcription with local Qwen3-ASR or Whisper (MLX on Apple Silicon), speaker diarization, transcript correction, structured meeting notes and StepFun TTS. StepFun ASR and TTS need an API key.

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.

Turns ComfyUI workflows into MCP tools with no code, covering generation and conversion across text, image, speech and video; works with local ComfyUI or RunningHub in the cloud. Start the server with uvx pixelle and configure an LLM first.

Open-source video translation and dubbing: transcribes lectures, courses and other videos, translates them into one of 33 languages, synthesizes a dub aligned to the picture, and can export SRT subtitles. Needs Python 3.10+, FFmpeg, the violin CLI and a pay-as-you-go Together AI API key.

Uses an LLM to translate SRT, ASS and VTT subtitles into any language in batches, convert formats and transcribe audio or video. Install the CLI from source (Python 3.10+); needs an API key (e.g. OpenRouter) or a local model, and subtitles go to that provider.