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.
Authors
- Dinesh Manocha (ORCID: https://orcid.org/0000-0001-7047-9801)
- Hermes Sampedro Llopis (ORCID: https://orcid.org/0000-0002-3172-332X)
- Steinar Guðjónsson
- Jackie Lin (ORCID: https://orcid.org/0000-0003-3087-2857)
- Haukur Hafsteinsson
- Paris Smaragdis
- Daniel Gert Nielsen (ORCID: https://orcid.org/0000-0002-7762-6568)
- Minje Kim (ORCID: https://orcid.org/0000-0003-3513-8328)
- Trausti Kristjansson
- Finnur Pind (ORCID: https://orcid.org/0000-0003-2779-2901)
- Georg Götz (ORCID: https://orcid.org/0000-0003-2896-5341)
- John R. Hershey
Institutions
- Google (United States) (US)
- Amazon (United States) (US)
- University of Illinois Urbana-Champaign (US)
- University of Maryland, College Park (US)
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
Funders
- National Science Foundation