The benefit of combining a deep neural network architecture with ideal ratio mask estimation in computational speech segregation to improve speech intelligibility

<p>Contains all the data:</p> <p>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.</p> <p>There are two folders:</p> <ol> <li><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)'</li> <li><strong>Masks:</strong> <ul> <li><strong>GMM-IBMs: </strong>IBMs and estimated IBMs for the models 'GMM', 'GMM (3 subbands)', 'GMM (7 subbands)', 'GMM (11 subbands)'</li> <li><strong>DNN-IBMs:</strong> IBMs and estimated IBMs for the models 'DNN (IBM)'; 'DNN (IBM, 40 ms)'</li> <li><strong>DNN-IRMs</strong>: IRMs and estimated IRMs for the models 'DNN (IRM)'; 'DNN (IRM, 40 ms)'</li> </ul> </li>