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arXiv · 2512.07872

LocaGen: Sub-Sample Time-Delay Learning for Beam Localization

Ishaan Kunwar·Henry Cantor·Tyler Rizzo·Ayaan Qayyum
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Abstract

The goal of LocaGen is to improve the localization performance of audio signals in the 2-D beam localization problem. LocaGen reduces sampling quantization errors through machine learning models trained on realistic synthetic data generated by a simulation. The system increases the accuracy of both direction-of-arrival (DOA) and precise location estimation of an audio beam from an array of three microphones. We demonstrate LocaGen's efficacy on a low-powered embedded system with an increased localization accuracy with a minimal increase in real-time resource usage. LocaGen was demonstrated to reduce DOA error by approximately 67% even with a microphone array of only 10 kHz in audio processing.

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Ishaan Kunwar, Henry Cantor, Tyler Rizzo, Ayaan Qayyum. 2025-11-27. LocaGen: Sub-Sample Time-Delay Learning for Beam Localization. https://arxiv.org/abs/2512.07872

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