whisper-1's verbose response carries a start and an end for every segment,
and the file tab was reading only the start, to build the [mm:ss] prefix.
Keeping the end as well is all an SRT needs.
The text stays the authority on wording and the segments on timing; they
meet at that prefix, which the cleanup model is already told to leave alone.
So a transcript that went through cleanup still turns into properly timed
subtitles. A line whose stamp matches no segment runs until the next line
starts, a line with no stamp at all joins the cue above it, and an end that
would run into the next cue is trimmed back.
The button is dead until a timestamped run finishes, because without
timestamps there are no segments to time anything with.
OpenRouter mirrors OpenAI's /audio/transcriptions field for field, so one
multipart request serves both providers and only the key, the base URL and
the model id change. That puts a dozen speech models behind the key that was
already there for the cleanup, and makes a single OpenRouter key enough for
the whole chain.
Its transcription endpoint takes no hint field, so the words from Cleanup
rules are not sent there; they still reach the cleanup model as a glossary.
Timestamps switch to openai/whisper-1, the namespaced id of the only model
that returns segment times.
The API tab is now grouped by role rather than by service, because a key no
longer belongs to a single job: both keys sit at the top, the two jobs below.
Each provider keeps its own model, so switching back and forth does not
overwrite the other one's.
The screenshots were downscaled to 430 px wide, which made the UI text
blurry. Restore them at native 1292 px as lossless WebP, which is also
half the size of the original PNGs (72 KB against 155 KB for the largest).
Rewrite every em dash in prose, comments, docstrings and interface strings
as ordinary punctuation.
Ctrl+Space starts and stops a recording. The audio goes to OpenAI for
transcription, a model on OpenRouter strips the fillers and restores
punctuation, and the result is copied and pasted into the focused window.
Only the Python standard library and PyQt6 — HTTP, multipart uploads and
WAV writing are all hand-rolled.
- pw-record captures raw 16 kHz mono PCM with a live level meter
- the corner indicator is drawn through XWayland, since a Wayland client
cannot position its own window
- silence is caught before it costs an API call, relative to each
recording's own noise floor, plus a filter for the stock phrases models
invent when handed silence
- audio and video files can be transcribed too, optionally with [mm:ss]
timestamps, chunked through ffmpeg for long inputs
- global shortcut installs as a KDE custom shortcut, with an evdev
listener as a fallback until the session is restarted
- Turkish and English interface, following the system locale by default
yusufipk