AutoEQ: Automatic Equalization for Speakers, Headphones, and Rooms

Introduction

AutoEQ and RoomEQ are Rust CLIs for computing corrections.

• AutoEQ does parametric EQ corrections for headphones and anechoic measurements of speakers (Spinorama or CEA2034).
• RoomEQ does room correction for stereo systems up to multi-channel systems and multi-subwoofer systems. It can generate IIR, FIR and hybrid filters and optimise for single or multiple positions.

Note: A graphical desktop application is available in a separate repository: SotF

Documentation

AutoEQ

• AutoEQ Manual — user guide for speaker and headphone EQ

RoomEQ

• RoomEQ 101 — getting started with RoomEQ concepts and workflow
• RoomEQ Manual — complete user guide for multi-channel room correction
• RoomEQ Input Format — JSON configuration schema and examples
• RoomEQ Output Format — filter output and DSP chain description

General

• References — papers, algorithms, and measurement resources

Capabilities

Supported Use Cases

• Speaker EQ: Optimize parametric EQ for loudspeakers using CEA2034/Spinorama measurements from spinorama.org
• Headphone EQ: Generate EQ corrections for headphones targeting Harman curves or custom targets
• Multi-Channel Systems: Optimize stereo, 2.1, and multi-driver configurations with crossover management
• Room Correction: Multi-subwoofer alignment and Double Bass Array (DBA) optimization
• Supporting-Source Room Compensation: Use a delayed, decorrelated supporting loudspeaker to fill reverberant energy without altering the primary source's direct sound (Brooks-Park room compensation)

Optimization Algorithms

Library	Algorithms	Constraint Support
Metaheuristics	DE, PSO, RGA, TLBO, Firefly	Penalty-based
AutoEQ Custom	Adaptive Differential Evolution	Nonlinear constraints
Pure-Rust	COBYLA, ISRES, CMA-ES	Nonlinear/bound constraints

Loss Functions

• speaker-flat: Minimize deviation from target curve (near-field listening)
• speaker-score: Maximize Harman/Olive preference score (far-field listening)
• headphone-flat: Flatten headphone response to target
• headphone-score: Optimize headphone preference score
• drivers-flat: Multi-driver crossover optimization
• multi-sub-flat: Multi-subwoofer array optimization

PEQ Filter Models

• pk: All peak/bell filters (default)
• hp-pk: Highpass + peak filters
• hp-pk-lp: Highpass + peaks + lowpass
• ls-pk-hs: Low shelf + peaks + high shelf
• free: All filters can be any type

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AutoEQ CLI

The autoeq binary optimizes EQ for individual speakers (anechoic) or headphones.

See the AutoEQ Manual for usage, parameters, algorithm selection, and examples.

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RoomEQ CLI

The roomeq binary optimizes multi-channel speaker systems with JSON configuration.

See the RoomEQ Manual, Input Format, and Output Format for complete documentation.

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Installation

If you do not have cargo already, install it with rustup. Cargo is a Rust package manager. Then:

cargo install autoeq \
   --bin autoeq \
   --bin roomeq \
   --bin autoeq-download-speakers \
   --bin convert-recording

Development

Prerequisites

Install rustup and just:

cargo install just

Build Commands

just                  # List available commands
just prod             # Build all release binaries
just prod-autoeq      # Build autoeq only
just prod-roomeq      # Build roomeq only
just dev              # Build debug binaries

Testing

# Check all targets
cargo check --lib --bins --tests --examples

# Run all tests
just test

# Run tests with nextest (faster)
just ntest

# Run specific test
cargo test --lib test_name

# Run tests for the autoeq package
cargo test -p autoeq --lib

Fuzzing

Fuzz targets are in fuzz/fuzz_targets/ (if present):

• autoeq_config.rs: Fuzzes configuration/CSV parsing
• autoeq_csv.rs: Fuzzes CSV input handling

To run fuzzing (requires nightly Rust and cargo-fuzz):

cargo install cargo-fuzz
cargo +nightly fuzz run autoeq_csv

Quality Assurance

The QA suite runs optimization scenarios with regression thresholds:

just qa-autoeq
just qa-roomeq

This executes predefined scenarios testing:

• Speaker optimization (flat and score loss)
• Headphone optimization (multiple algorithms)
• Various PEQ models and algorithm combinations

Each scenario has a --qa <threshold> flag that fails if the final loss exceeds the threshold.

Individual QA targets:

just qa-ascilab-6b           # Speaker with score loss
just qa-jbl-m2-flat          # Speaker with flat loss
just qa-jbl-m2-score         # Speaker with score loss
just qa-beyerdynamic-dt1990pro  # Headphone tests
just qa-edifierw830nb        # Multiple algorithm comparison

Benchmarking

# Download speaker data from spinorama.org
just download-speakers

# Run algorithm benchmarks
just bench-autoeq-speaker

Code Quality

just fmt              # Format code
just lint             # Run clippy with warnings as errors
cargo check --lib --bins --tests --examples
cargo clippy --all -- -D warnings

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Contributing

• Open an issue on GitHub
• Send a PR