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Representation learning strategies to model pathological speech: Effect of multiple spectral resolutions., , , and . Comput. Speech Lang., (April 2024)Towards an automatic monitoring of the neurological state of Parkinson's patients from speech., , , , , , , and . ICASSP, page 6490-6494. IEEE, (2016)Phonation and Articulation Analyses in Laryngeal Pathologies, Cleft Lip and Palate, and Parkinson's Disease., , , and . IWINAC (2), volume 10338 of Lecture Notes in Computer Science, page 424-434. Springer, (2017)Evaluation of wavelet measures on automatic detection of emotion in noisy and telephony speech signals., , , , , and . ICCST, page 1-6. IEEE, (2014)Multi-channel Convolutional Neural Networks for Automatic Detection of Speech Deficits in Cochlear Implant Users., , , , , and . CIARP, volume 11896 of Lecture Notes in Computer Science, page 679-687. Springer, (2019)Articulation and Empirical Mode Decomposition Features in Diadochokinetic Exercises for the Speech Assessment of Parkinson's Disease Patients., , , , , and . CIARP, volume 11896 of Lecture Notes in Computer Science, page 688-696. Springer, (2019)Automatic detection of parkinson's disease from continuous speech recorded in non-controlled noise conditions., , , , , and . INTERSPEECH, page 105-109. ISCA, (2015)Influence of the Interviewer on the Automatic Assessment of Alzheimer's Disease in the Context of the ADReSSo Challenge., , , , , , , , and . Interspeech, page 3785-3789. ISCA, (2021)Feature Space Visualization with Spatial Similarity Maps for Pathological Speech Data., , , and . INTERSPEECH, page 3068-3072. ISCA, (2019)Multi-channel spectrograms for speech processing applications using deep learning methods., , , , , and . Pattern Anal. Appl., 24 (2): 423-431 (2021)