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Evaluation of the Neurological State of People with Parkinson's Disease Using i-Vectors., , , , and . INTERSPEECH, page 299-303. ISCA, (2017)A Comprehensive Approach for Security Assessment in Transport., , , , and . CRITIS, volume 8985 of Lecture Notes in Computer Science, page 37-42. Springer, (2014)Multimodal I-vectors to Detect and Evaluate Parkinson's Disease., , , and . INTERSPEECH, page 2349-2353. ISCA, (2018)Language Independent Assessment of Motor Impairments of Patients with Parkinson's Disease Using i-Vectors., , , , and . TSD, volume 10415 of Lecture Notes in Computer Science, page 147-155. Springer, (2017)Emotion recognition from speech under environmental noise conditions using wavelet decomposition., , , , , and . ICCST, page 247-252. IEEE, (2015)Automatic Detection of Parkinson's Disease from Compressed Speech Recordings., , , and . TSD, volume 9302 of Lecture Notes in Computer Science, page 88-95. Springer, (2015)Evaluation of wavelet measures on automatic detection of emotion in noisy and telephony speech signals., , , , , and . ICCST, page 1-6. IEEE, (2014)A Non-linear Dynamics Approach to Classify Gait Signals of Patients with Parkinson's Disease., , , , , and . WEA (2), volume 916 of Communications in Computer and Information Science, page 268-278. Springer, (2018)Phonological i-Vectors to Detect Parkinson's Disease., , , , , and . TSD, volume 11107 of Lecture Notes in Computer Science, page 462-470. Springer, (2018)Phonological Posteriors and GRU Recurrent Units to Assess Speech Impairments of Patients with Parkinson's Disease., , , , and . TSD, volume 11107 of Lecture Notes in Computer Science, page 453-461. Springer, (2018)