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

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 atthis https URL.
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