AP3
Learning OS

AI + voice + audio / learning project

Voice liner notes

A grounded listening conversation that keeps source, state, interruption, and playback ownership visible.

Overview

A working notebook for turning a question into a thing that can be tested, felt, and improved.

Problem

A music companion can deepen a listener's relationship with a song, but an unconstrained model can invent context, compete with the music, or control playback unpredictably.

Goals

  • Separate verified artist context, catalog metadata, model inference, and unknown information.
  • Use deterministic tools for search and playback commands.
  • Make streaming, interruption, cancellation, ducking, resume, and errors visible and recoverable.

Architecture

Artist-approved context and catalog metadata → retrieval and structured tools → streaming model response → explicit voice state → canonical playback commands.

Design

The companion should feel like a layer of liner notes around the music, not a chat product placed on top of it.

Implementation

Prototype with fixture context first. Add tool calls, interruption, and evaluation cases before expanding memory or personality.

Lessons

  • Grounding is an interface problem as much as a retrieval problem.
  • Voice needs visible state and predictable silence.

Future improvements

Explore artist-facing tools and shared listening only after trust, interruption, and recovery are dependable.