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

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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Publication Details

Published
2025-04-06
DOI
https://doi.org/10.1109/icasspw65056.2025.11011109
Citations
4
Primary Topic
Speech Recognition and Synthesis
Type
article
Field-Weighted Citation Impact
9.92

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article

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

Dinesh Manocha, Hermes Sampedro Llopis, Steinar Guðjónsson, Jackie Lin et al.
4 citations
Speech Recognition and Synthesis
9.92
article

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

Dinesh Manocha, Hermes Sampedro Llopis, Steinar Guðjónsson, Jackie Lin, Haukur Hafsteinsson, Paris Smaragdis, Daniel Gert Nielsen, Minje Kim, Trausti Kristjansson, Finnur Pind, Georg Götz, John R. Hershey
article en
4 citations

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.

Google (United States) (US), Amazon (United States) (US), University of Illinois Urbana-Champaign (US), University of Maryland, College Park (US)
National Science Foundation
Openalex Percentile: Top 2%
Speech Recognition and Synthesis
9.92
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