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Automatic Classification of Parkinson's Disease Using Wav2vec Embeddings at Phoneme, Syllable, and Word Levels., , , , and . TSD (2), volume 15049 of Lecture Notes in Computer Science, page 313-323. Springer, (2024)Federated Learning for Secure Development of AI Models for Parkinson's Disease Detection Using Speech from Different Languages., , , , , , and . INTERSPEECH, page 5003-5007. ISCA, (2023)Apkinson: A Mobile Solution for Multimodal Assessment of Patients with Parkinson's Disease., , , , , , , , , and 5 other author(s). INTERSPEECH, page 964-965. ISCA, (2019)Automatic Classification of Hypokinetic and Hyperkinetic Dysarthria based on GMM-Supervectors., , , and . INTERSPEECH, page 2368-2372. ISCA, (2023)An Automatic Multimodal Approach to Analyze Linguistic and Acoustic Cues on Parkinson's Disease Patients., , , , , and . INTERSPEECH, page 1703-1707. ISCA, (2023)Transfer Learning to Detect Parkinson's Disease from Speech In Different Languages Using Convolutional Neural Networks with Layer Freezing., , , and . TDS, volume 12284 of Lecture Notes in Computer Science, page 331-339. Springer, (2020)Feature Representation of Pathophysiology of Parkinsonian Dysarthria., , , , , and . INTERSPEECH, page 3048-3052. ISCA, (2019)Robust Classification of Parkinson's Speech: an Approximation to a Scenario With Non-controlled Acoustic Conditions., , , , and . TSD (2), volume 15049 of Lecture Notes in Computer Science, page 252-262. Springer, (2024)End-to-End Parkinson's Disease Detection Using a Deep Convolutional Recurrent Network., , , and . TSD, volume 13502 of Lecture Notes in Computer Science, page 326-338. Springer, (2022)