jcvasquezc/PDS_2019.2

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jcvasquezc/PDS_2019.2

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Ejercicios y Laboratorios del curso "Procesamiento digital de señales". Universidad de Antioquia, 2019-2

DisVoice

feature extraction from speech signals

Jupyter Notebook

NeuroSpeech

Toolkit to asses speech impairments in patients with neurological disorders

AEspeech

Feature extraction from speech signals based on representation learning strategies using pre-trained autoencoders

SMA2

Sorce code of Apkinson: android app to monitor the motor symptoms of Parkinson's patients

Corr_Dim

Compute the Correlation Dimension of a Time Series

SARHA

Speech recognition using KALDI for assessment of patological speech

images_deep_transition

This is a complementary material of the paper "Multimodal assessment of Parkinson’s disease: a deep learning approach" submitted to IEEE transactions on Biomedical engineering

colomb-ia-supervised-emoDB

Reto aprendizaje supervisado Colomb-ia

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