[FEATURE] FluidMeet: use the custom dictionary in meeting transcripts
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Assessment
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Newbie friendliness
- 50/100
- Issue type
- Feature
- Clarity
- Clearly specified
- Activity status
- Active
- Tech stack
- swift
- Domain
- audio-video-rtc, documentation
Research direction
Start in Sources/Fluid/Services/Meeting/MeetingProcessingPipeline.swift near line 1429, where the meeting configuration is built with only the language, then check Sources/Fluid/Services/FluidAudioProvider.swift lines 146-154, where vocabulary boosting and dictionary rewriting are rejected as unsupportedFeature. Done means custom words and replacements apply to meeting transcripts on first processing and re-transcription, or the dictionary settings state clearly that they apply to dictation only.
Written by the indexing model from the issue text.
Description
Custom words and replacements from the dictionary work in dictation but never reach meeting transcripts. I'd like FluidMeet to use them too.
Meetings are where I most need them. Calls are full of product and people names, and the meeting model spells them a new way each time. In one 38-minute call the same product name came out six different ways ("Space Fest", "Spacefest", "SpaceFast" and others), and a coworker's name was misspelled.
From the code, this looks like a known gap, not a bug. The meeting pipeline builds its configuration with only the language (MeetingProcessingPipeline.swift#L1429), so vocabulary boosting and dictionary rewriting default to off. The meeting provider also rejects both as unsupportedFeature (FluidAudioProvider.swift#L146-L154).
Two requests:
- Apply custom words and replacements to meeting transcripts, both when the call is first processed and when it's re-transcribed.
- Until that ships, say in the dictionary settings that it applies to dictation only. The dictionary screen never mentions meetings, so nothing tells you they skip it.
Setup: FluidVoice 1.6.12-beta.1, macOS 27.0.1, Apple Silicon. Meeting model parakeet-tdt-v2.
- Dominant language
- Swift
- Stars
- 11.9k
- Forks
- 863
- Avg merge
- 2d 54m
- Merged PRs (30d)
- 42
Getting set up
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First steps
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