v0.36.0

A Vietnamese-and-English meeting came back as Chinese, Hebrew and
Japanese, with a Vietnamese line subtitled into Vietnamese. This is that
report, traced to the end.

The specialist was locked out by the guess it exists to correct

The first reading was "whisper-tiny is too poor — warn, or refuse to
record". That was wrong, and the user said so: gipformer was installed,
and several Vietnamese lines in the very same transcript are perfect.
The specialist was running. The question was why it did not run on the
lines that were broken.

Because routing asked whisper which language each sentence was, and
refused every specialist that did not claim the answer. Whisper-tiny
answered zh, he, ja, ru — nothing claims those, so the rescue
path was shut. Above two seconds the wrong answer was actively
believed.

The languages you name are now what decides. A language you declared
gets its specialist whatever the fast model guessed; the guess only
decides which specialist is tried first. Whether an answer is kept is
settled by what the model produced, not by what anything claimed — a
specialist fed a language it does not speak goes quiet, measured at 15
characters against 146, and that silence is the referee.

If you name no languages, nothing changes: there is no better signal
than the guess.

A rescued line kept the wrong label, so it was translated wrongly

A specialist reports no language — there is nothing for it to choose
between — so a Vietnamese line it had just rescued kept whisper's zh.
That label decides which way a line is translated, which is why Các cái nguồn lực came back subtitled Carregla in Vietnamese. A specialist
that has been heard now stamps the language it speaks.

And the subtitle already drawn against the wrong label is removed once
the language is known — in what you are reading and in the subtitle files
on disk.

The loop filter could not see Chinese or Japanese

今天今天今天… twenty-four times, with Vietnamese and English subtitles
of it. The repetition guard splits on spaces, and that text has none, so
the whole loop was one word and slipped under every threshold. It now
reads scripts without word spaces properly, and catches a loop that
starts partway through a sentence — a model does not usually begin stuck,
it says something and then jams.

And the screen

• Minimised showed no words at all. The meter is sized by its
  container; as a bare row item it took the whole strip. The line is
  back, and the translation with it — which is what you shrink the window
  for.
• The settings panel sat open over the transcript. "Đang ghi + config
  to quá không xem được transcribe." It folds now, and the control that
  opens it says what is behind it rather than reading "Đổi".
• "Tải model (0 MB)" did nothing when pressed — a language with no
  specialist in the registry has no model to download. It says that in
  words now, without a button.
• The status line names every model doing the listening, not just the
  first, so "why is the Vietnamese right and the English not" is
  answerable from the screen.
• The transcript gets a reading measure and sets translations in against
  a rule, instead of three near-identical greys per line.

Still true, and worth saying

Translation with SMALL100 is sentence by sentence: that model's interface
takes one line and has no place to put context. Contextual translation
needs the LLM path, and that is the next piece of work rather than
something claimed here.