The Benefit Of Combining A Deep Neural Network Architecture With Ideal Ratio Mask Estimation In Computational Speech Segregation To Improve Speech Intelligibility

Contains all the data: Bentsen, T., T.May, A. A. Kresnner, and T. Dau. The benefit of combining<br> a deep neural network architecture with ideal ratio mask estimation<br> in computational speech segregation to improve speech intelligibility.<br> PLOS ONE., in review. There are two folders: <strong>WRSs:</strong> the Word Recognition Scores (WRSs) from the listener study. The matrix has dimensions 9 conditions x 20 subjects. Data is ordered corresponding to the following condition order:<br> 'UP', 'GMM', 'GMM (3 subbands)', 'GMM (7 subbands)', 'GMM (11 subbands)', 'DNN (IBM)'; 'DNN (IBM, 40 ms)'; 'DNN (IRM)'; 'DNN (IRM, 40 ms)' <strong>Masks:</strong> <strong>GMM-IBMs: </strong>IBMs and estimated IBMs for the models 'GMM', 'GMM (3 subbands)', 'GMM (7 subbands)', 'GMM (11 subbands)' <strong>DNN-IBMs:</strong> IBMs and estimated IBMs for the models 'DNN (IBM)'; 'DNN (IBM, 40 ms)' <strong>DNN-IRMs</strong>: IRMs and estimated IRMs for the models 'DNN (IRM)'; 'DNN (IRM, 40 ms)'