# Transcribe

Requires Bash, FFmpeg, curl, jq, Python 3, and standard coreutils. Keep
`chunks.py`, `subtitles.py`, and `transcript.py` beside the script. The API key is read using
the 1Password CLI (`op`) from `op://API Keys/openrouter-mai-transcribe-2/credential`.

```sh
./transcribe recording.m4a
./transcribe video.mp4 > transcript.txt
./transcribe --srt video.mp4 > subtitles.srt
./transcribe --no-diarization recording.m4a > transcript.txt
./transcribe --srt --no-diarization video.mp4 > subtitles.srt
./transcribe --chunk-minutes 10 too_long.webm > transcript.txt
```

Accepts m4a, mp4, aac, flac, opus, mp3, ogg, wav, and other formats your
FFmpeg supports. Uses the first audio track, converts it to mono 16 kHz MP3
at 64 kbps (requires FFmpeg's libmp3lame encoder),
and sends it to OpenRouter's `microsoft/mai-transcribe-2` model. Temporary
files are removed on exit. The transcript goes to stdout; progress and errors
go to stderr. Output is emitted only after all requests and conversion succeed.

Speaker diarization is **enabled by default** through
`provider.options.azure.diarization.enabled`, following
[OpenRouter's speaker diarization API](https://openrouter.ai/docs/guides/overview/multimodal/stt#verbose-transcripts-timestamps-and-speakers).
Use `--no-diarization` to explicitly disable it for every request, with either
plain text or `--srt` output. Text output prints returned IDs above each paragraph:

```text
[Speaker 0]
How did you get started?

[Speaker 1]
It was a long time ago.
```

Text wraps at 80 columns (except an unusually long unbroken word), with blank
lines at speaker changes and pauses of at least two seconds. Long turns split
at sentence endings after about 400 characters, or at 800 characters even
without punctuation. The formatter preserves the words and their order.
Unlabelled passages use `[Speaker unknown]` when other words have labels; a
response without any labels is printed without speaker markers. A warning on
stderr reports missing or incomplete labels when diarization was requested.
Speaker IDs come from the provider; they are not names or inferred from text.
SRT uses labels to break cues at speaker changes but does not print the IDs.

Long recordings are automatically split into uploads of at most **10 minutes**
with diarization, or **30 minutes** with `--no-diarization`, including overlap
and MP3 padding. These defaults account for
[Microsoft's documented diarization failures around 15 minutes and longer](https://learn.microsoft.com/en-us/azure/ai-services/speech-service/mai-transcribe).
Use `--chunk-minutes N` (an integer from 1 to 30) to override the limit in either
mode. Larger chunks with diarization may fail with a timeout or
`diarization_unavailable`; reduce the chunk size or use `--no-diarization`.
At 64 kbps, a 10-minute upload is about 4.8 MB of MP3 or 6.4 MB of base64;
a 30-minute upload is about 14.4 MB of MP3 or 19.2 MB of base64.
These are local defaults, not guaranteed provider limits:
[OpenRouter documents a 60-second processing timeout](https://openrouter.ai/docs/guides/overview/multimodal/stt),
so reduce the chunk size if requests still time out.

For each boundary, the script looks for a pause of at least 0.3 seconds in the
last 30 seconds before the limit, using a -35 dBFS peak threshold. It joins in
the middle of the last suitable pause, or at the duration boundary if there is
no pause. Each upload includes three seconds beyond the join, so neighbouring
uploads share six seconds of audio even during continuous speech. The duration
cap includes this overlap; the next chunk starts before the previous one ends.

Requests with diarization and all chunked requests ask for word timestamps,
including for plain text. Short requests with `--no-diarization` retain the
provider's existing text line breaks and add wrapping to long lines.
The script matches words and their times in the overlap, switches transcripts
at a shared word, and keeps the repeated passage once. It prefers a matching
phrase to distinguish intentional repetitions. If no words match, it uses
timestamp ownership and warns when speech near the join needs review. Overlap
protects words at the audio cuts, but recognition errors or inaccurate model
timestamps can still require corrections. Missing or invalid word timestamps
are an error. Plain text for a chunked recording is assembled from the words.

SRT timestamps are shifted back to the original recording's timeline before
cue generation, with continuous cue numbering. Speaker labels, when returned,
are local to each request; text marks them as `[Chunk 1, Speaker 0]`,
`[Chunk 2, Speaker 0]`, etc. The same ID in different chunks does **not** establish
that it is the same person. The script does not identify speakers across
chunks. Short recordings still use one request and use `[Speaker 0]` markers.

Audio is first decoded to temporary mono 16 kHz PCM (about 115 MB per hour),
so all cuts share the same sample clock even when container duration metadata
is missing. Only one MP3 chunk and its request payload are staged at a time.
Requests run sequentially. A failed request stops the run; there is no automatic
retry or resume, and rerunning sends the earlier chunks again.

`--srt` requests word timestamps using OpenRouter's `verbose_json` response.
Words are grouped into cues of at most two lines (42 characters per line,
except an unusually long unbroken word) and six seconds. Cues also break at
sentence endings, pauses of at least 0.7 seconds, and speaker changes when
speaker labels are available. Timing comes from the words, rounded to
milliseconds. If word start times move backwards, they are clamped to the
preceding word's start without reordering the transcript; end times are extended
to the adjusted start only when needed. Subtitle output goes to stdout; missing
or invalid word timestamps produce an error. Without `--srt`, output remains
plain text.

One input file per invocation. To run the local regression tests:

```sh
python3 -B -m unittest -v
```

[OpenRouter model and API reference](https://openrouter.ai/microsoft/mai-transcribe-2)