The benefit of combining a deep neural network architecture with ideal ratio mask estimation in computational speech segregation to improve speech intelligibility
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下载链接:
https://zenodo.org/record/1202205
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资源简介:
Contains all the data:
Bentsen, T., T.May, A. A. Kresnner, and T. Dau. The benefit of combining
a deep neural network architecture with ideal ratio mask estimation
in computational speech segregation to improve speech intelligibility.
PLOS ONE., in review.
There are two folders:
WRSs: 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:
'UP', 'GMM', 'GMM (3 subbands)', 'GMM (7 subbands)', 'GMM (11 subbands)', 'DNN (IBM)'; 'DNN (IBM, 40 ms)'; 'DNN (IRM)'; 'DNN (IRM, 40 ms)'
Masks:
GMM-IBMs: IBMs and estimated IBMs for the models 'GMM', 'GMM (3 subbands)', 'GMM (7 subbands)', 'GMM (11 subbands)'
DNN-IBMs: IBMs and estimated IBMs for the models 'DNN (IBM)'; 'DNN (IBM, 40 ms)'
DNN-IRMs: IRMs and estimated IRMs for the models 'DNN (IRM)'; 'DNN (IRM, 40 ms)'
创建时间:
2020-01-24



