Tomas Arias-Vergara

Latest

• Influence of the Interviewer on the Automatic Assessment of Alzheimer's Disease in the Context of the ADReSSo Challenge.
• Nonlinear dynamics and Poincaré sections to model gait impairments in different stages of Parkinson’s disease
• Convolutional Neural Networks and a Transfer Learning Strategy to Classify Parkinson’s Disease from Speech in Three Different Languages
• Multi-channel Convolutional Neural Networks for Automatic Detection of Speech Deficits in Cochlear Implant Users
• Surgical mask detection with deep recurrent phonetic models
• A Multitask Learning Approach to Assess the Dysarthria Severity in Patients with Parkinson's Disease
• A Non-linear Dynamics Approach to Classify Gait Signals of Patients with Parkinson’s Disease
• Apkinson: A Mobile Solution for Multimodal Assessment of Patients with Parkinson's Disease
• Automatic Intelligibility Assessment of Parkinson's Disease with Diadochokinetic Exercises
• Multimodal assessment of Parkinson's disease: a deep learning approach
• Phonological i-Vectors to Detect Parkinson's Disease
• Speaker models for monitoring Parkinson’s disease progression considering different communication channels and acoustic conditions
• Unobtrusive Monitoring of Speech Impairments of Parkinson's Disease Patients Through Mobile Devices
• Apkinson-A Mobile Monitoring Solution for Parkinson's Disease.
• Parkinson's disease and aging: analysis of their effect in phonation and articulation of speech
• Speaker Model to Monitor the Neurological State and the Dysarthria Level of Patients with Parkinson’s Disease
• Gender-dependent gmm-ubm for tracking parkinson's disease progression from speech
• Parkinson's Disease Progression Assessment from Speech Using GMM-UBM.
• Wavelet-based time-frequency representations for automatic recognition of emotions from speech
• Automatic detection of Parkinson's disease from continuous speech recorded in non-controlled noise conditions