# Maximum Likelihood Estimation of the Direction of Sound In A Reverberant Noisy Environment

arXiv: https://arxiv.org/abs/2406.17103 · HTML: https://mlsanity.com/paper/2406.17103/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 18 references that are in the map.
- First posted on arXiv 24 Jun 2024.

## Builds on (most cited first, 4 of 4)

- [Sound Event Localization and Detection of Overlapping Sources Using Convolutional Recurrent Neural Networks](https://mlsanity.com/paper/1807.00129/) (2018)
- [A Survey of Sound Source Localization with Deep Learning Methods](https://mlsanity.com/paper/2109.03465/) (2021)
- [Time Domain Velocity Vector for Retracing the Multipath Propagation](https://mlsanity.com/paper/2006.02099/) (2020)
- [On Acoustic Modeling for Broadband Beamforming](https://mlsanity.com/paper/1904.08971/) (2019)

## Abstract (arXiv)

We describe a new method for estimating the direction of sound in a reverberant environment from basic principles of sound propagation. The method utilizes SNR-adaptive features from time-delay and energy of the directional components after acoustic wave decomposition of the observed sound field to estimate the line-of-sight direction under noisy and reverberant conditions. The effectiveness of the approach is established with measured data of different microphone array configurations under various usage scenarios.