Sound field image dataset

<strong>Description</strong> This <strong>sound field image dataset</strong> contains clean-noisy pairs of complex-valued sound-field images generated by 2D acoustic simulations. The dataset was initially prepared for <strong>deep sound-field denoiser </strong>(https://github.com/nttcslab/deep-sound-field-denoiser)<strong>,</strong> a DNN-based denoising method for optically measured sound fields. Since the data is a two-dimensional sound field based on the Helmholtz equation, one can use this dataset for any acoustic application. Please check our GitHub repository and paper for details. <strong>Directory structure</strong> The dataset contains three directories: training, validation, and evaluation. Each directory contains "soundsource#" sub-directories (# represents the number of sound sources used in the acoustic simulation). Each sub-directory has three h5 files for data (clean, white noise, and speckle noise) and three CSV files listing random parameter values used in the simulation. - /training - /soundsource# - constants.csv - random_variable_ranges.csv - random_variables.csv - sf_true.h5 - sf_noise_white.h5 - sf_noise_speckle.h5 <strong>Condition of use</strong> This dataset is available under the attached license file. Read the terms and conditions in NTTSoftwareLicenseAgreement.pdf carefully. <strong>Citation</strong> If you use this dataset, please cite the following paper. K. Ishikawa, D. Takeuchi, N. Harada, and T. Moriya ``Deep sound-field denoiser: optically-measured sound-field denoising using deep neural network,'' arXiv:2304.14923 (2023).