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End-2-End Modeling of Speech and Gait from Patients with Parkinson's Disease: Comparison Between High Quality Vs. Smartphone Data.

, , , , , and . ICASSP, page 7298-7302. IEEE, (2021)

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Parkinson's Disease and Aging: Analysis of Their Effect in Phonation and Articulation of Speech., , and . Cogn. Comput., 9 (6): 731-748 (2017)Evaluation of effectiveness in conversations between humans and chatbots using parallel convolutional neural networks with multiple temporal resolutions., , and . Multim. Tools Appl., 83 (2): 5473-5492 (January 2024)Depression assessment in people with Parkinson's disease: The combination of acoustic features and natural language processing., , , , , , and . Speech Commun., (2022)Representation learning strategies to model pathological speech: Effect of multiple spectral resolutions., , , and . Comput. Speech Lang., (April 2024)Federated learning for secure development of AI models for Parkinson's disease detection using speech from different languages., , , , , , and . CoRR, (2023)Characterization Methods for the Detection of Multiple Voice Disorders: Neurological, Functional, and Laryngeal Diseases., , , , , , , , and . IEEE J. Biomed. Health Informatics, 19 (6): 1820-1828 (2015)Assessing Parkinson's Disease from Speech Using Fisher Vectors., , and . INTERSPEECH, page 3063-3067. ISCA, (2019)Apkinson: A Mobile Solution for Multimodal Assessment of Patients with Parkinson's Disease., , , , , , , , , and 5 other author(s). INTERSPEECH, page 964-965. ISCA, (2019)Cross-lingual Self-Supervised Speech Representations for Improved Dysarthric Speech Recognition., , , , , and . INTERSPEECH, page 51-55. ISCA, (2022)Automatic detection of parkinson's disease from continuous speech recorded in non-controlled noise conditions., , , , , and . INTERSPEECH, page 105-109. ISCA, (2015)