# Extending GCC-PHAT using Shift Equivariant Neural Networks

arXiv: https://arxiv.org/abs/2208.04654 · HTML: https://mlsanity.com/paper/2208.04654/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- Builds on 14 of its 27 references that are in the map.
- First posted on arXiv 9 Aug 2022.

## Builds on (most cited first, 14 of 14)

- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift](https://mlsanity.com/paper/1502.03167/) (2015)
- [Speaker Recognition from Raw Waveform with SincNet](https://mlsanity.com/paper/1808.00158/) (2018)
- [On Translation Invariance in CNNs: Convolutional Layers can Exploit Absolute Spatial Location](https://mlsanity.com/paper/2003.07064/) (2020)
- [Pyroomacoustics: A Python package for audio room simulations and array processing algorithms](https://mlsanity.com/paper/1710.04196/) (2017)
- [A Survey of Sound Source Localization with Deep Learning Methods](https://mlsanity.com/paper/2109.03465/) (2021)
- [Deep Neural Networks for Multiple Speaker Detection and Localization](https://mlsanity.com/paper/1711.11565/) (2017)
- [Broadband DOA estimation using Convolutional neural networks trained with noise signals](https://mlsanity.com/paper/1705.00919/) (2017)
- [Robust Sound Source Tracking Using SRP-PHAT and 3D Convolutional Neural Networks](https://mlsanity.com/paper/2006.09006/) (2020)
- [Towards End-to-End Acoustic Localization using Deep Learning: from Audio Signal to Source Position Coordinates](https://mlsanity.com/paper/1807.11094/) (2018)
- [Reverberant Sound Localization with a Robot Head Based on Direct-Path Relative Transfer Function](https://mlsanity.com/paper/2012.03574/) (2020)
- [A General Network Architecture for Sound Event Localization and Detection Using Transfer Learning and Recurrent Neural Network](https://mlsanity.com/paper/2011.07859/) (2020)
- [Time Difference of Arrival Estimation from Frequency-Sliding Generalized Cross-Correlations Using Convolutional Neural Networks](https://mlsanity.com/paper/2002.00641/) (2020)
- [Frequency-Sliding Generalized Cross-Correlation: A Sub-band Time Delay Estimation Approach](https://mlsanity.com/paper/1910.08838/) (2019)

## Built on by (most cited first, 7 of 7)

- [DSpAST: Disentangled Representations for Spatial Audio Reasoning with Large Language Models](https://mlsanity.com/paper/2509.13927/) (2025)
- [wav2pos: Sound Source Localization using Masked Autoencoders](https://mlsanity.com/paper/2408.15771/) (2024)
- [Learning Multi-Target TDOA Features for Sound Event Localization and Detection](https://mlsanity.com/paper/2408.17166/) (2024)
- [StofNet: Super-resolution Time of Flight Network](https://mlsanity.com/paper/2308.12009/) (2023)
- [SONNET: Enhancing Time Delay Estimation by Leveraging Simulated Audio](https://mlsanity.com/paper/2411.13179/) (2024)
- [Efficient and Microphone-Fault-Tolerant 3D Sound Source Localization](https://mlsanity.com/paper/2505.20961/) (2025)
- [What Do Neural Networks Learn for TDOA Estimation? A Cross-Architecture Probing Study](https://mlsanity.com/paper/2606.22020/) (2026)

## Abstract (arXiv)

Speaker localization using microphone arrays depends on accurate time delay estimation techniques. For decades, methods based on the generalized cross correlation with phase transform (GCC-PHAT) have been widely adopted for this purpose. Recently, the GCC-PHAT has also been used to provide input features to neural networks in order to remove the effects of noise and reverberation, but at the cost of losing theoretical guarantees in noise-free conditions. We propose a novel approach to extending the GCC-PHAT, where the received signals are filtered using a shift equivariant neural network that preserves the timing information contained in the signals. By extensive experiments we show that our model consistently reduces the error of the GCC-PHAT in adverse environments, with guarantees of exact time delay recovery in ideal conditions.