Generative Data Augmentation Challenge: Synthesis of Room Acoustics for Speaker Distance Estimation

Jackie Lin; Georg Götz; Hermes Sampedro Llopis; Haukur Hafsteinsson; Steinar Guðjónsson; Daniel Gert Nielsen; Finnur Pind; Paris Smaragdis; Dinesh Manocha; John Hershey; Trausti Kristjansson; Minje Kim

arXiv · 2501.13250

Generative Data Augmentation Challenge: Synthesis of Room Acoustics for Speaker Distance Estimation

Jackie Lin·Georg Götz·Hermes Sampedro Llopis·Haukur Hafsteinsson·Steinar Guðjónsson·Daniel Gert Nielsen·Finnur Pind·Paris Smaragdis·Dinesh Manocha·John Hershey·Trausti Kristjansson·Minje Kim

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Abstract

This paper describes the synthesis of the room acoustics challenge as a part of the generative data augmentation workshop at ICASSP 2025. The challenge defines a unique generative task that is designed to improve the quantity and diversity of the room impulse responses dataset so that it can be used for spatially sensitive downstream tasks: speaker distance estimation. The challenge identifies the technical difficulty in measuring or simulating many rooms' acoustic characteristics precisely. As a solution, it proposes generative data augmentation as an alternative that can potentially be used to improve various downstream tasks. The challenge website, dataset, and evaluation code are available at https://sites.google.com/view/genda2025.

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Jackie Lin, Georg Götz, Hermes Sampedro Llopis, Haukur Hafsteinsson, Steinar Guðjónsson, Daniel Gert Nielsen, Finnur Pind, Paris Smaragdis, Dinesh Manocha, John Hershey, Trausti Kristjansson, Minje Kim. 2025-01-22. Generative Data Augmentation Challenge: Synthesis of Room Acoustics for Speaker Distance Estimation. https://arxiv.org/abs/2501.13250

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