Activities per year
The sound field in a room is often modeled as a superposition of elementary waves, such as plane or spherical waves. These wave expansions provide a powerful means to interpolate or extrapolate the sound field within (and outside) the measurement domain. However, projecting the sound field of a large domain in a room on a planar or spherical wave base yields a high number of very elemental components. We examine the use of dictionary learning to find a set of alternative basis functions that are suitable to represent the sound field enclosed in a room. The resulting dictionary is able to capture the dominant features of the sound field, and represent it using only a sparse set of functions, the dictionary atoms. In this study, high resolution measurements of the sound pressure in a room are simulated and used as a training set to learn a dictionary. We analyze the spatial properties of the learned dictionary, and compare it to simple elementary basis functions such as plane and spherical waves.
|Title of host publication||Proceedings of the 23rd International Congress on Acoustics|
|Publisher||Deutsche Gesellschaft für Akustik e.V.|
|Publication status||Published - 2019|
|Event||23rd International Congress on Acoustics - Eurogress, Aachen , Germany|
Duration: 9 Sep 2019 → 13 Sep 2019
|Conference||23rd International Congress on Acoustics|
|Period||09/09/2019 → 13/09/2019|
Bibliographical noteAvailable online: http://pub.dega-akustik.de/ICA2019/data/articles/001187.pdf )
- Sounds field reconstruction
- Room acoustics
- Dictionary learning
9 Sep 2019
Activity: Talks and presentations › Conference presentations
Hahmann, M., Verburg Riezu, S. A., & Fernandez-Grande, E. (2019). Analysis of a sound field in a room using dictionary learning. In Proceedings of the 23rd International Congress on Acoustics (pp. 149-154). Deutsche Gesellschaft für Akustik e.V..