Juan Camilo Vasquez Correa
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Elmar Nöth
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Influence of the Interviewer on the Automatic Assessment of Alzheimer's Disease in the Context of the ADReSSo Challenge.
Current methods and new trends in signal processing and pattern recognition for the automatic assessment of motor impairments: the case of Parkinson's disease
Nonlinear dynamics and Poincaré sections to model gait impairments in different stages of Parkinson’s disease
Multi-channel Convolutional Neural Networks for Automatic Detection of Speech Deficits in Cochlear Implant Users
Feature Representation of Pathophysiology of Parkinsonian Dysarthria
Natural Language Analysis to Detect Parkinson's Disease
Feature Space Visualization with Spatial Similarity Maps for Pathological Speech Data
Analysis and evaluation of handwriting in patients with Parkinson’s disease using kinematic, geometrical, and non-linear features
Automated Cross-language Intelligibility Analysis of Parkinson’s Disease Patients Using Speech Recognition Technologies
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
Automatic Intelligibility Assessment of Parkinson's Disease with Diadochokinetic Exercises
Multimodal assessment of Parkinson's disease: a deep learning approach
Multimodal I-vectors to Detect and Evaluate Parkinson's Disease
Phonological i-Vectors to Detect Parkinson's Disease
Speaker models for monitoring Parkinson’s disease progression considering different communication channels and acoustic conditions
Towards an automatic evaluation of the dysarthria level of patients with Parkinson's disease
Unobtrusive Monitoring of Speech Impairments of Parkinson's Disease Patients Through Mobile Devices
Apkinson-A Mobile Monitoring Solution for Parkinson's Disease.
Characterisation of voice quality of Parkinson’s disease using differential phonological posterior features
Convolutional Neural Network to Model Articulation Impairments in Patients with Parkinson's Disease.
Effect of acoustic conditions on algorithms to detect Parkinson's disease from speech
Language independent assessment of motor impairments of patients with Parkinson’s disease using i-vectors
Multi-view representation learning via GCCA for multimodal analysis of Parkinson's disease
On the impact of non-modal phonation on phonological features
Speaker Model to Monitor the Neurological State and the Dysarthria Level of Patients with Parkinson’s Disease
Automatic detection of hypernasal speech of children with cleft lip and palate from spanish vowels and words using classical measures and nonlinear analysis
Gender-dependent gmm-ubm for tracking parkinson's disease progression from speech
Non-linear dynamics characterization from wavelet packet transform for automatic recognition of emotional speech
Parkinson's Disease Progression Assessment from Speech Using GMM-UBM.
Towards an automatic monitoring of the neurological state of Parkinson's patients from speech
Word accuracy and dynamic time warping to assess intelligibility deficits in patients with parkinsons disease
Automatic detection of Parkinson's disease from continuous speech recorded in non-controlled noise conditions
Emotion recognition from speech under environmental noise conditions using wavelet decomposition
Time dependent ARMA for automatic recognition of fear-type emotions in speech
New computer aided device for real time analysis of speech of people with Parkinson's disease
Design and implementation of an embedded system for real time analysis of speech from people with parkinson's disease
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