Juan Camilo Vasquez-Correa

Latest

• On Modeling Glottal Source Information for Phonation Assessment in Parkinson’s Disease
• Influence of the Interviewer on the Automatic Assessment of Alzheimer's Disease in the Context of the ADReSSo Challenge.
• Parallel Representation Learning for the Classification of Pathological Speech: Studies on Parkinson’s Disease and Cleft Lip and Palate
• Current methods and new trends in signal processing and pattern recognition for the automatic assessment of motor impairments: the case of Parkinson's disease
• Comparison of User Models Based on GMM-UBM and I-Vectors for Speech, Handwriting, and Gait Assessment of Parkinson’s Disease Patients
• Nonlinear dynamics and Poincaré sections to model gait impairments in different stages of Parkinson’s disease
• Identity Verification in Virtual Education Using Biometric Analysis Based on Keystroke Dynamics
• Word-Embeddings and Grammar Features to Detect Language Disorders in Alzheimer’s Disease Patients
• Apkinson: the smartphone application for telemonitoring Parkinson’s patients through speech, gait and hands movement
• Articulation and Empirical Mode Decomposition Features in Diadochokinetic Exercises for the Speech Assessment of Parkinson's Disease Patients
• 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
• Feature Representation of Pathophysiology of Parkinsonian Dysarthria
• Apkinson
• Disvoice
• Neurospeech
• Phonet
• Natural Language Analysis to Detect Parkinson's Disease
• Feature Space Visualization with Spatial Similarity Maps for Pathological Speech Data
• Phonet: A Tool Based on Gated Recurrent Neural Networks to Extract Phonological Posteriors from Speech
• Surgical mask detection with deep recurrent phonetic models
• 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
• 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
• Multimodal I-vectors to Detect and Evaluate Parkinson's Disease
• NeuroSpeech: An open-source software for Parkinson's speech analysis
• Phonological i-Vectors to Detect Parkinson's Disease
• Representaciones tiempo-frecuencia basadas en sensores inerciales para caracterizar la marcha en la enfermedad de Parkinson
• 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
• Parkinson's disease and aging: analysis of their effect in phonation and articulation of speech
• Phonation and Articulation Analyses in Laryngeal Pathologies, Cleft Lip and Palate, and Parkinson’s Disease
• 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
• Emotion recognition from speech with acoustic, non-linear and wavelet-based features extracted in different acoustic conditions
• 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
• Wavelet-based time-frequency representations for automatic recognition of emotions 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
• Automatic emotion recognition in compressed speech using acoustic and non-linear features
• Emotion recognition from speech under environmental noise conditions using wavelet decomposition
• Time dependent ARMA for automatic recognition of fear-type emotions in speech
• Evaluation of the effects of speech enhancement algorithms on the detection of fundamental frequency of speech
• Evaluation of wavelet measures on automatic detection of emotion in noisy and telephony speech signals
• 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