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AutoEq

Generates EQ settings that adjust headphone sound toward a target curve, using measured data.

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Stars
16.4k
Forks
2.6k
Licence
MIT
Language
Python
Last update
6 days ago
Type
Library

What it is

AutoEq is a tool that calculates equalizer settings to correct how a pair of headphones sounds, based on published frequency response measurements. It produces settings for many equalizer apps but does not apply the equalization itself. The project offers a web app at autoeq.app for most users, plus a Python library and command line tool for developers.

  • Generate parametric EQ settings for a headphone model and import them into an equalizer app
  • Run the command line tool to produce EQ results and convolution filters for a given headphone measurement
  • Use the Python library to work with frequency response data and optimize parametric equalizers

Great for

  • People who want EQ settings for a headphone that has been measured by supported sources
  • Developers who want to script frequency response processing or EQ optimization in Python
  • Users who want to compare headphones against a chosen target curve

Not ideal for

  • Anyone wanting an app that applies EQ directly, since AutoEq only generates settings and another equalizer app is needed
  • Users of headphones not covered by the supported measurement sources, because the README says those are missing from the database
  • Non-developers who prefer not to use a terminal, since the README says the command line use is mainly intended for developers
Step-by-step guide: how to use AutoEqInstall, first run, examples, tips and FAQs

How to get it

  1. 1

    Clone and build from source

    You'll need: Git · Python 3 (64-bit) · libsndfile (only if needed for soundfile problems)

    Clone AutoEq

    git clone https://github.com/jaakkopasanen/AutoEq.git

    Go to AutoEq location

    cd AutoEq

    Create a python virtual environment

    python -m venv venv

    Install required packages

    python -m pip install -U -e .
  2. 2

    Run it

    • Activate the virtual environment (. venv/bin/activate on Linux and Mac, venv\Scripts\activate.bat on Windows)
    • Run python -m autoeq --help to confirm the installation lists the command line parameters
    • Run python -m autoeq with --input-file pointing to a measurement CSV and --output-dir set to a folder
    • Check the output folder for the generated results
  3. 3

    Get the most out of it

    • Use the --target option to choose a different frequency response target file from the targets folder
    • Try --parametric-eq with --parametric-eq-config to select filter configurations such as shelf filters
    • Use --convolution-eq or --ten-band-eq to produce other output formats, as shown in the README examples
    • Use --fs and --bit-depth to set sample rate and bit depth for convolution output

Downloads

Source code (.zip)master branch · straight from GitHub

Strengths

  • The web app at autoeq.app needs no installation, according to the README
  • Includes a collection of headphone measurements from several named sources
  • Available as a PyPI package for use in other Python projects

Trade-offs

  • The README says the GitHub repository now mainly serves developers, so the setup is technical
  • Only headphones measured by the supported sources can be processed
  • AutoEq does not apply the equalization itself and requires a separate app

Stats synced from GitHub. The assessment above was drafted with AI from the project's README on 2026-10-29 and may miss recent changes — check the README before relying on a command. MIT licence: free to use, modify and distribute, including commercially, as long as you keep the copyright notice.