meeting-assistant/ROADMAP.md

Roadmap

Next Milestone: Meeting Assistant MVP GUI

Build the user-facing application over the validated Meeting Lab Python API.

• select an existing audio file
• reliably import WAV, FLAC and M4A through canonical FFmpeg preparation
• offer optional audio normalization, enabled by default
• create and edit Meeting Context through structured fields
• add and manage present and mentioned_only people
• optionally map SPEAKER_XX labels to participants with explicit confirmation
• configure and start run_mvp_meeting(...)
• display stage-based status and real progress when available
• handle completed and failed runs clearly
• display and edit the detailed generated protocol
• export the reviewed protocol

The milestone must keep diarization, GPU acceleration and fixed-duration audio chunking optional. It must not launch the Meeting Lab CLI as a subprocess or duplicate Meeting Lab processing logic.

Complete real-meeting validation of this vertical slice before expanding the post-run workflow.

Following Milestone: Distribution Protocol

• derive or generate a shorter participant-facing version
• allow review and editing before distribution
• export both detailed and short versions
• retain provenance linking each version to its transcript, configuration, prompt and model where practical

Later Product Work

• speaker/name review with explicit human confirmation
• deterministic correction of suitable derived artifacts, beginning with a simple search-and-replace path
• protocol-only regeneration from existing transcription and diarization plus corrected mappings and Meeting Context
• transcript viewing and broader correction workflows
• recording and artifact lifecycle management
• search, tags, projects and meeting history
• richer Markdown, PDF and DOCX export
• optional SQLite indexing and full-text search
• integrated recording controls
• calendar and conferencing integrations
• semantic search and organizational knowledge features

Research and Optional Extensions

• live transcription and real-time summaries
• company glossary and custom vocabulary
• voice identification with explicit consent and confirmation
• automatic name and speaker suggestions only as non-authoritative candidates for later human review
• audio cleanup
• OCR for shared screens
• RAG and knowledge-graph integration
• multi-language meetings and translation
• dual-model or evidence pipelines only if later validation demonstrates a material reliability benefit