# Reflection-Aware Sound Source Localization

arXiv: https://arxiv.org/abs/1711.07791 · HTML: https://mlsanity.com/paper/1711.07791/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Nov 2017.

## Built on by (most cited first, 5 of 5)

- [Structure from Silence: Learning Scene Structure from Ambient Sound](https://mlsanity.com/paper/2111.05846/) (2021)
- [The Boombox: Visual Reconstruction from Acoustic Vibrations](https://mlsanity.com/paper/2105.08052/) (2021)
- [SonicSieve: Bringing Directional Speech Extraction to Smartphones Using Acoustic Microstructures](https://mlsanity.com/paper/2504.10793/) (2025)
- [A Review on Sound Source Localization in Robotics: Focusing on Deep Learning Methods](https://mlsanity.com/paper/2507.01143/) (2025)
- [Audio Simulation for Sound Source Localization in Virtual Evironment](https://mlsanity.com/paper/2404.01611/) (2024)

## Abstract (arXiv)

We present a novel, reflection-aware method for 3D sound localization in indoor environments. Unlike prior approaches, which are mainly based on continuous sound signals from a stationary source, our formulation is designed to localize the position instantaneously from signals within a single frame. We consider direct sound and indirect sound signals that reach the microphones after reflecting off surfaces such as ceilings or walls. We then generate and trace direct and reflected acoustic paths using inverse acoustic ray tracing and utilize these paths with Monte Carlo localization to estimate a 3D sound source position. We have implemented our method on a robot with a cube-shaped microphone array and tested it against different settings with continuous and intermittent sound signals with a stationary or a mobile source. Across different settings, our approach can localize the sound with an average distance error of 0.8m tested in a room of 7m by 7m area with 3m height, including a mobile and non-line-of-sight sound source. We also reveal that the modeling of indirect rays increases the localization accuracy by 40% compared to only using direct acoustic rays.