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On the deficiency of intelligibility metrics as proxies for subjective intelligibility.

, , , , and . Speech Commun., (May 2023)

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On Training Targets and Objective Functions for Deep-Learning-Based Audio-Visual Speech Enhancement., , , and . CoRR, (2018)Latent Dirichlet mixture model., , and . Neurocomputing, (2018)Noise Condition-Dependent Training Based on Noise Classification and SNR Estimation., , , and . IEEE Trans. Speech Audio Process., 15 (8): 2431-2443 (2007)Adaptive Multi-Frame-Rate Scheme for Distributed Speech Recognition Based on a Half Frame-Rate Front-End., , and . MMSP, page 1-4. IEEE, (2005)Binary pattern flavored feature extractors for Facial Expression Recognition: An overview., , , and . MIPRO, page 1131-1137. IEEE, (2015)Introduction to the Issue on Speech Processing for Natural Interaction With Intelligent Environments., , , , and . J. Sel. Topics Signal Processing, 4 (5): 769-771 (2010)A non-intrusive Short-Time Objective Intelligibility measure., , , and . ICASSP, page 5085-5089. IEEE, (2017)A method for predicting the intelligibility of noisy and non-linearly enhanced binaural speech., , , and . ICASSP, page 4995-4999. IEEE, (2016)Bias-Compensated Informed Sound Source Localization Using Relative Transfer Functions., , , and . IEEE ACM Trans. Audio Speech Lang. Process., 26 (7): 1271-1285 (2018)Joint Separation and Denoising of Noisy Multi-talker Speech using Recurrent Neural Networks and Permutation Invariant Training., , , and . CoRR, (2017)