• Products
  • Studio
  • Engine
  • Research
  • Work with us
Request access

Audio machine learning and creative sensing

  • What an audio model learns
  • How models see audio
  • Stem separation
  • Audio generation
  • Neural instruments and timbre transfer
  • Camera and gesture control
  • Adding a model to your app

Build your own tools

  • Signals and systems
  • Anatomy of a Maru module
  • Build an effect
  • Build an instrument
  • Build a MIDI tool
  • Realtime and numerical safety
  • Testing sound and behaviour
  • Presets, state and automation
  • Shipping to browser and plugins
  • Building with an AI agent

Instrument design and publishing

  • What makes an instrument inspiring
  • Controls, macros and ranges
  • Presets as product design
  • Interface and first use
  • Finding an audience
  • Identity and story
  • Demos, pricing and launch
  • Rights and maintenance
  1. Learn
  2. Build and share
  3. What an audio model learns

Audio machine learning and creative sensing

What an audio model learns

Training, inference and why a model's output is an estimate

Coming soon

This guide isn't published yet. It will be a hands-on guide with sounds to play and something to make. Browse the rest of Build and share in the meantime.

Next How models see audio

Products

  • All products
  • Plugins
  • Sounds
  • Bundles
  • Studio

Engine

  • Engine overview
  • Build with the Engine
  • Documentation
  • Sampler
  • Hardware
  • Symbolic
  • UI Kit
  • Plugin examples
  • Comparisons

Made for

  • Producers
  • Sound designers
  • Artists
  • Web developers
  • Product teams
  • Hackathon teams
  • Researchers
  • More

Company

  • About
  • Work with us
  • Call for artists
  • Learn
  • Research
  • Jobs
  • Contact
  • Blog

Legal

  • Terms
  • Privacy
Instagram (opens in a new tab)GitHub (opens in a new tab)

Building the future of sound, with you.

© 2026 Maru · private early access