DynamicSound simulator for simulating moving sources and microphone arrays

TL;DR

DynamicSound is an open-source simulation framework that generates realistic, moving-source, multichannel spatial audio for developing and testing sound localization and spatial audio algorithms, addressing limitations of existing static, indoor-focused simulators.

Contribution

The paper introduces DynamicSound, a novel simulation system that models moving sound sources and microphones with high spatial fidelity, including Doppler effects and environmental reflections, for the first time in an open-source tool.

Findings

Generated signals maintain high spatial fidelity across conditions.

DynamicSound accurately reproduces inter-microphone delays and spectral effects.

Comparative evaluations show superior realism over existing simulators.

Abstract

Developing algorithms for sound classification, detection, and localization requires large amounts of flexible and realistic audio data, especially when leveraging modern machine learning and beamforming techniques. However, most existing acoustic simulators are tailored for indoor environments and are limited to static sound sources, making them unsuitable for scenarios involving moving sources, moving microphones, or long-distance propagation. This paper presents DynamicSound an open-source acoustic simulation framework for generating multichannel audio from one or more sound sources with the possibility to move them continuously in three-dimensional space and recorded by arbitrarily configured microphone arrays. The proposed model explicitly accounts for finite sound propagation delays, Doppler effects, distance-dependent attenuation, air absorption, and first-order reflections from planar surfaces, yielding temporally consistent spatial audio signals. Unlike conventional mono or stereo simulators, the proposed system synthesizes audio for an arbitrary number of virtual microphones, accurately reproducing inter-microphone time delays, level differences, and spectral coloration induced by the environment. Comparative evaluations with existing open-source tools demonstrate that the generated signals preserve high spatial fidelity across varying source positions and acoustic conditions. By enabling the generation of realistic multichannel audio under controlled and repeatable conditions, the proposed open framework provides a flexible and reproducible tool for the development, training, and evaluation of modern spatial audio and sound-source localization algorithms.