Irregular Linear Array Results
In this page we show results corresponding to reproduction of a single source when using the deep learning-based model presented in [1], denoted as CNN, the Model-based rendering technique presented in [2] denoted as MR and the pressure-matching approach [3] and the adaptive wavefield synthesis technique[4], denoted as AWFS. We also present results related to an adaptive version of MR denoted AMR. We consider a regular loudspeaker array of 64 elements and randomly remove 16,32, and 48 loudspeakers, ending with a 48,32,16 element array, respectively
Setup
In the image we show the setup used to generate the training and test data.
Ground truth
48 loudspeaker setup
32 loudspeaker setup
16 loudspeaker setup
References
[1] Comanducci, L. Antonacci, F., & Sarti. A., Synthesis of Soundfields through Irregular Loudspeaker Arrays Based on Convolutional Neural Networks [arXiv preprint].
[2] Bianchi, L., Antonacci, F., Sarti, A., & Tubaro, S. (2016). Model-based acoustic rendering based on plane wave decomposition. Applied Acoustics, 104, 127-134.
[3] Nelson, P. A. (1994). Active control of acoustic fields and the reproduction of sound. Journal of Sound and Vibration, 177(4), 447-477.
[4] Gauthier, Philippe-Aubert, and Alain Berry. “Adaptive wave field synthesis with independent radiation mode control for active sound field reproduction: Theory.” The Journal of the Acoustical Society of America 119.5 (2006): 2721-2737.
Support or Contact
For any information regarding the paper or the code send us an email at luca.comanducci@polimi.it!