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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)Feature Space Visualization with Spatial Similarity Maps for Pathological Speech Data., , , and . INTERSPEECH, page 3068-3072. 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)The INTERSPEECH 2019 Computational Paralinguistics Challenge: Styrian Dialects, Continuous Sleepiness, Baby Sounds & Orca Activity., , , , , , , , , and 8 other author(s). INTERSPEECH, page 2378-2382. ISCA, (2019)A microphone-independent visualization technique for speech disorders., , , , and . INTERSPEECH, page 951-954. ISCA, (2009)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)