feat(app): add custom vocabulary support for Parakeet CTC boosting#77
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feat(app): add custom vocabulary support for Parakeet CTC boosting#77
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Voice Activity Detection removes silence before transcription, improving accuracy and speed for recordings with significant pauses. Uses FluidAudio's Silero VAD v6 model (CoreML/ANE) to detect speech regions, then: - Extracts speech-only audio for transcription - Remaps timestamps back to original timeline New types: SpeechRegion, VadSegmentMap (pure, testable), FluidVAD (wrapper). Settings: vadEnabled (default off), vadThreshold (0.3–0.9 slider). Pipeline: single-source path preprocesses with VAD when enabled. Inspired by @execsumo's work in #70.
Enable domain-specific vocabulary boosting for the Parakeet ASR engine using FluidAudio's CTC keyword spotting pipeline. After TDT transcription, the CTC model runs constrained decoding to detect and correct vocabulary terms (e.g. company names, product names) that TDT may have misrecognized. - Add customVocabularyPath to AppSettings (persisted via UserDefaults) - Add configureVocabulary() to ParakeetEngine that loads vocab file, downloads CTC models, and initializes VocabularyRescorer - Apply CTC rescoring post-transcription in transcribeSegments() - Add vocabulary file picker in SettingsView (Parakeet section) - Wire customVocabularyPath from AppSettings to ParakeetEngine in AppState - Add CustomVocabularyTests (7 tests: defaults, persistence, engine wiring) - Update Package.resolved to match main branch (FluidAudio 0.13.4) Inspired by @execsumo's work in #70.
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Summary
Inspired by @execsumo's work in #70.
Stacked on #76 (VAD)
Test plan