whosaid

whosaid

Local, speaker-attributed transcription for Apple Silicon — who said what, on your Mac, nothing leaves the machine.

whosaid pairs Whisper speech-to-text with speaker diarization to turn a meeting, interview, call, or podcast recording into a transcript that says *who spoke when* — running fully offline and on-device on an Apple Silicon Mac, with no cloud service, no API keys, and no Hugging Face token. Think of it as whisper + speaker labels + voice-based speaker recognition, in one command.

Example output (meeting.speakers.txt):

[00:00:04] Alice: Thanks for jumping on, I know it's late for you.

[00:00:11] SPEAKER_01: No problem at all, happy to make it work. [00:00:19] Alice: Let's start with the roadmap for next quarter. [00:00:27] SPEAKER_01: Sounds good, I've got a few updates on that.

Why whosaid

• Meetings, interviews, calls, podcasts — get a transcript where every turn is attributed to a person, not just a wall of text.
• Privacy by construction — audio, text, and voice embeddings never leave your Mac. The only cloud step is one you opt into: [summarizer] engine = "claude" sends each transcript's text to Anthropic to draft action items. Leave it unset and nothing is sent.
• Your name on your own lines — a one-time ~45s voice enrollment teaches whosaid your voice, so your turns read as your name instead of SPEAKER_00.
• Tells you how many people spoke — the number of distinct speakers is auto-detected and reported up front, with per-speaker turn counts and talk time.
• Speaker cards to identify who's who — for every speaker, whosaid writes a card of that voice's most representative snippets, so you can read a few lines and know who was talking.
• Remembers people you name — identify a speaker once with whosaid relabel, and their voiceprint is saved to a private local registry so they're auto-named in every future transcript.
• Fast on long recordings — recordings over ~15 min are diarized in parallel windows and stitched back into consistent speakers by voiceprint, so an 80-minute meeting is minutes, not tens of minutes, recovering the same speakers as a single-pass run.
• No accounts, no API keys, no Hugging Face token — every model comes from an open, ungated source.
• Search everything you have recorded. whosaid index builds a local full-text (and, with Ollama, meaning) index over every transcript in a meeting workspace; whosaid search finds the turn, whosaid context shows the minute around it, and whosaid graph answers who committed to what, when. See Search your meetings.
• Hands-free from Voice Memos. whosaid watch install puts a launchd agent on the Voice Memos folder (or any folder): stop recording, and a few minutes later the meeting is transcribed, summarized, and searchable. See Hands-free ingest.
• Usable from an AI agent, too. whosaid mcp exposes transcribe, relabel, doctor, and the read-only workspace search tools as MCP tools for Claude Code, Claude Desktop, Kiro, and other MCP clients, with the same local-only guarantee as the CLI.

How it compares

Looking for a MacWhisper, whisperX, or aTrain alternative? If you want speaker-attributed transcription that runs fully offline on Apple Silicon and can put real *names* on voices — not just SPEAKER_00 labels — that's the gap whosaid fills. Here's how it stacks up:

Quickstart

git clone https://github.com/sblattj/whosaid && cd whosaid   # get the code

./bootstrap.sh # check deps, download models, install ~/.local/bin/whosaid whosaid enroll # ~45s reading a printed passage — teaches whosaid your voice whosaid path/to/meeting.m4a # transcribe + diarize + label -> meeting.speakers.txt (and friends)

If ~/.local/bin is not on your shell's PATH, add it or invoke the installed command by its absolute path. WHOSAID_INSTALL_DIR=/another/bin ./whosaid install selects another install directory. The installed command is a symlink to the checkout, so updating the checkout updates the command without copying or duplicating the implementation.

whosaid's helper scripts need Python 3.11 or newer, because whosaid.toml is read with tomllib. The launcher picks one interpreter: $WHOSAID_PYTHON if it is set, otherwise the first of python3, python3.13, python3.12 and python3.11 on your PATH that is 3.11+, otherwise uv python find '>=3.11'. It skips the stock macOS python3 (3.9) automatically. If no interpreter qualifies, commands that run Python stop with an error; uv python install 3.13 fixes that. whosaid doctor shows which interpreter was picked.

Homebrew is optional when uv, ffmpeg, and ffprobe are already installed. The launcher and watcher search ~/.local/bin, ~/bin, and ~/homebrew/bin as well as the usual system prefixes. Setup can install a pinned, checksum-verified Apple Silicon uv archive into ~/.local/bin. Homebrew FFmpeg installation requires a bottle; a nonstandard prefix will not silently trigger a source build.

For a Mac without Homebrew, or one where no bottle is available, use:

./bootstrap.sh --build-ffmpeg

This builds pinned FFmpeg source into user-local ffmpeg and ffprobe executables. It needs Apple's Command Line Tools (xcode-select --install if missing), compilation time, and free disk space, but no administrator-owned install prefix or GPG installation. The source archive is checked with macOS shasum against a checksum verified from FFmpeg's signed release. Existing usable tools are retained. Setup then warms the Python environments and downloads the models as usual.

Commands

| whosaid relabel --auto [--forget NAME ...] [--fold-unknown] | Re-apply naming to an existing transcript with no assignments: re-runs registry matching + the absorb pass over the cached sidecar (and the voices/ enrollment clips, as transcribe does) and rewrites the transcript + cards. Picks up voices enrolled after the transcript was made, and drops auto-assigned names whose registry entry and clip are gone. --forget NAME (repeatable) clears NAME from this meeting first; it can come back if NAME is still enrolled and matches. Add --fold-unknown to repair anonymous phantom clusters in cached auto-diarization; it requires --auto and does not assign an identity.