Hickson, Lorraine (2019) Study of the relationship between speech and Obstructive Sleep Apnea using Deep Learning techniques PRE - Research Project, ENSTA.
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Abstract
In this study, Machine Learning techniques are applied to the diagnosis of Obstructive sleep apnea (OSA) based on patient voices samples. These data are represented as Mel Cepstral Coefficients (MFCC). Among others, Convolutional Neural Networks (CNN) and data augmentation were used.
Item Type: | Thesis (PRE - Research Project) |
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Subjects: | Information and Communication Sciences and Technologies |
ID Code: | 7439 |
Deposited By: | Lorraine Hickson |
Deposited On: | 09 juin 2021 16:11 |
Dernière modification: | 09 juin 2021 16:11 |
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