filmcraft/docs/transcripts.md

Transcripts and text-based editing

FilmCraft's Text panel ▸ Transcript tab shows the dialogue of the open sequence as text. Select words to mark In/Out, then extract or lift them; remove filler words and long pauses in one step; turn the transcript into captions. Every action is an engine command (transcript.*), so the CLI, the control channel and MCP agents can do the same.

Model

• A transcript belongs to a media item (Project::transcripts, saved in the .fcproj since schema v9). It lists words with media-time bounds (Ticks), an optional speaker index and a confidence, plus the speaker names and the language. Because the times are media time, the transcript stays valid however the clip is trimmed, moved, sped up or reused.
• The sequence transcript is derived, never stored (filmcraft_edit::transcript::sequence_words): audio tracks are read top first; a word is heard through the first enabled clip whose range covers the word's midpoint (duplicates of the same dialogue on lower tracks read once); disabled, reversed and frame-hold clips contribute nothing.
• Speaker names come from the clip transcripts, so renaming "Speaker 1" in every transcript renames it across the sequence.

Commands

Command	What it does
transcript.generate	Transcribe media items (items, else the Project selection, else the media of the sequence's audio clips). Params: model (default whisper-base), language (auto = detect), diarize, maxSpeakers. One undo step.
transcript.set	Store a transcript you bring (JSON: language, speakers, words with text/start/end/speaker); it is sorted and made well formed.
transcript.delete	Remove transcripts.
transcript.inspect	The sequence transcript: words (index, text, sequence times, speaker, clip), paragraphs, speakers, the word at the playhead.
transcript.search	Word-index ranges matching a phrase (case and punctuation ignored; the last word may be a prefix).
transcript.select	Mark In/Out around words from..=to (frame-snapped outward) and move the playhead there.
transcript.extract / transcript.lift	Extract (ripple) or lift the words' frames on the targeted tracks.
transcript.renameSpeaker	Rename a speaker by name (every transcript) or by index in one item.
transcript.removeFillers	Ripple-delete filler words (fillers, default um/uh/erm/…; phrases such as "you know" allowed).
transcript.removePauses	Ripple-delete pauses longer than minSeconds, keeping keepSeconds of air on both sides.
transcript.createCaptions	Lay the words out as captions on a new caption track (maxChars, lines, minSeconds, maxSeconds, gapFrames).
transcript.models / transcript.downloadModel	List the speech models (size, licence, installed) / download one.

Speech recognition

Recognition goes through the Transcriber trait (crates/speech). The built-in recogniser is OpenAI's Whisper, run in pure Rust on candle on the CPU, with timestamp decoding, language detection and word times from cross-attention alignment (see the filmcraft_speech::whisper module docs). Speakers are labelled by clustering per-chunk MFCC statistics (filmcraft_speech::diarize); no model is involved.

Both are optional features, off by default and never built for the web:

• whisper (on filmcraft-speech, filmcraft-engine, and the filmcraft / filmcraft-cli apps, where it also enables downloads): candle inference.
• download (speech-download on the engine): HTTPS downloads with rustls + RustCrypto and the operating system's certificate verifier.

Without whisper, and with no recogniser installed, transcript.generate and Transcribe Sequence are disabled, with "speech-to-text is not available in this build" as the reason (describe, command_list {"enabled_only": true} and the menus show it); with Automatically transcribe clips on, file.import reports the same reason as a transcription: … entry in its errors. Without speech-download, transcript.downloadModel is disabled the same way. Transcripts can still be imported with transcript.set and edited with every other command. Hosts and tests can install any recogniser in Session::transcriber, which enables transcription in any build.

Models

Weights are never bundled or committed. They are downloaded on request into <data dir>/models/<id>/ (see filmcraft_engine::autosave::default_data_dir), each file pinned to a revision of OpenAI's Hugging Face repositories and checked against its SHA-256:

Id	Languages	Licence
whisper-tiny	multilingual	MIT (OpenAI); HF conversion Apache-2.0
whisper-base (default)	multilingual	MIT (OpenAI); HF conversion Apache-2.0
whisper-small	multilingual	MIT (OpenAI); HF conversion Apache-2.0

Testing

Unit and engine tests use a fake Transcriber (FixedTranscriber), so CI needs no model. The end-to-end test crates/speech/tests/whisper_model.rs (feature whisper) runs only when weights are in target/models/<id>/ (or $FILMCRAFT_MODELS_DIR) and speech samples (mono 16 kHz f32 with a reference .txt) are in target/fixtures/speech/; it reports the word error rate and otherwise prints SKIPPED. Measured on 2026-10-01: whisper-tiny, English, 12.2 % WER over 797 words of the local speech samples (LibriSpeech read speech and dialogue clips) (about 9.5 minutes for the run in a release build on an Apple-silicon laptop CPU).

Limits

• Transcription runs synchronously inside the command (no background job or progress bar yet).
• Track items that refer to a subclip are looked up by the subclip's id, so a transcript made for the parent media is not shown through subclip clips yet.