Rust/clippy 1.99 added `chunks_exact_to_as_chunks` and tightened
`needless_late_init` and `drain_collect`, failing `clippy -D warnings`
on main.
- `chunks_exact(N)` / `chunks_exact_mut(N)` with a constant N become
`as_chunks::<N>()` / `as_chunks_mut::<N>()` (fixed-size arrays, so
several byte reads drop their per-element indexing). relink's
fingerprint uses the `(chunks, remainder)` split; its hash output is
unchanged.
- Late-initialised `let`s in ac3 bit allocation and opus CELT
bands/rate become `let x = if/match …`.
- `dpb.drain(..).collect()` becomes `std::mem::take(&mut dpb)`.
No behaviour change; `cargo xtask ci` passes.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
- crates/speech (L2): Transcriber trait, FixedTranscriber, Whisper model catalogue (pinned,
SHA-256 verified) with optional downloader (feature `download`: ureq + rustls + RustCrypto),
pure-Rust Whisper inference on candle with word timestamps (feature `whisper`), log-mel, VAD
word tightening, MFCC speaker clustering. Both features off by default and for wasm.
- project: per-media-item transcripts (Project::transcripts); schema v9 with a no-op v8->v9
migration and a v8 fixture.
- edit::transcript: sequence transcript derived from clip transcripts, search, paragraphs,
word ranges, pause/filler detection, ripple delete of many ranges, caption layout.
- engine: transcript.* commands (generate, set, delete, inspect, search, select, extract, lift,
renameSpeaker, removeFillers, removePauses, createCaptions, models, downloadModel);
Session::transcriber for hosts/tests; features `whisper` / `speech-download` (also on the
desktop and CLI apps). Without whisper, transcript.generate fails with a clear error.
- ui: Text panel Transcript tab (Transcribe button, speaker paragraphs of clickable words,
Shift+click selection -> In/Out, extract/lift/remove fillers/create captions, search) with
text.transcript.* automation ids; headless UI test.
- docs/transcripts.md, crates/speech/README.md, architecture and project-files updates.
whisper-tiny measures 12.2% WER over 797 words on local samples.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
