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Dossier Transcriber

A local pipeline for turning tabletop RPG recordings into accurate, timestamped transcripts and AI-assisted session summaries.

Designed for long-form tabletop sessions such as Delta Green campaigns.

Goals

  • Convert session recordings into high-quality transcripts
  • Support both single-track and multi-track recordings
  • Preserve timestamps and recording context
  • Produce portable transcript formats
  • Keep processing modular and tool-agnostic
  • Provide optional AI-assisted analysis (future)

Current Status

Completed ✅

Core Pipeline

  • Python project setup with uv
  • Typer CLI
  • Rich logging and progress output
  • TOML configuration system
  • FFmpeg audio extraction
  • Audio validation
  • Audio chunking with overlap
  • Faster-Whisper transcription backend
  • Configurable transcription models
  • CPU inference
  • Timestamped transcript segments
  • Initial prompt support
  • Basic progress reporting

Roadmap

Phase 1 — Transcript Artifact

Phase 1 — Artifact System

  • Define artifact directory structure
  • Define JSON schemas
    • Audio artifact
    • Chunk manifest
    • Chunk transcript
    • Final transcript
  • Add artifact versioning
  • Add artifact loading/saving

Goal:

Have a reliable machine-readable transcript that every other feature consumes.


Phase 2 — Recording & Audio Support

Support real-world tabletop recording setups.

Multi Track

  • Track metadata
    • Stream index
    • Channel information
    • Speaker label
  • Transcribe tracks independently
  • Compile transcripts chronologically
  • Preserve speaker information

Supported workflows:

  • OBS recordings
  • Discord recordings
  • Craig multi-track exports
  • Standard video files

Phase 3 — Export System

Convert transcript artifacts into usable formats.

  • JSON export
  • Markdown export
  • Plain text export
  • Export templates
  • Human-readable formatting
  • Speaker formatting

Examples:

[00:12:42] Marcus:
You arrive at the Macallistar Building...

[00:12:55] Morgan:
I check the apartment.

Phase 4 — Transcription Quality

Improve transcript accuracy.

  • Prompt template system

    • Game system terminology
    • Campaign terminology
    • Character/NPC names
    • Locations
    • Language-specific hints
  • Configurable transcription parameters

  • Rolling context prompts

  • Transcript cleanup/post-processing

  • Better handling of slang and proper nouns

Future:

  • GPU acceleration

Phase 5 — Pipeline Architecture

Make Dossier usable as a repeatable processing tool.

  • Independent pipeline stages
  • Resume interrupted jobs
  • Skip completed stages
  • Cache completed stages
  • Re-run individual stages
  • Support for multiple transcriptions of the same file (for testing parameters, for ex)

Examples:

dossier audio session.mkv
dossier transcribe session/
dossier export session/
dossier analyze session/
  • Batch processing
  • Job manifests

Phase 6 — AI Session Analysis

Optional AI-powered features.

Summaries

  • Short recap
  • Detailed recap
  • Scene breakdown
  • Important events
  • Character moments
  • Player decisions

Structured Extraction

  • Characters/NPCs
  • Locations
  • Organizations
  • Items
  • Clues
  • Important terminology
  • Unresolved threads

Timeline

  • Chronological events
  • Key moments with timestamps
  • Decisions and consequences

Phase 7 — Quality & Maintenance

Improve long-term usability.

  • Better error handling
  • Logging system
  • Performance benchmarks
  • Documentation
  • Example configurations
  • Test suite

Nice To Have

Search

  • Full-text transcript search
  • Semantic search
  • Local RAG over sessions

Presentation

  • HTML transcript viewer
  • PDF export
  • Audio ↔ transcript synchronization

Design Principles

  • JSON should be the source of truth.
  • Each pipeline stage should be independent.
  • Transcription, export, and analysis should remain separate.
  • LLM usage should be optional.
  • Configuration should be preferred over hardcoded behavior.
  • External integrations (Obsidian, databases, etc.) are outside the scope of Dossier.
  • Multi-track recordings should be preferred over automatic diarization when available.

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