Noninvasive Deep Learning Analysis for Smith–Magenis Syndrome Classification

Noninvasive Deep Learning Analysis for Smith–Magenis Syndrome Classification

Smith–Magenis syndrome (SMS) is a rare, underdiagnosed condition due to limited public awareness of genetic testing and a lengthy diagnostic process. Voice analysis can be a noninvasive tool for monitoring and detecting SMS. In this paper, the cepstral peak prominence and mel-frequency cepstral coef...

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Bibliographic Details
Main Authors: Esther Núñez-Vidal, Raúl Fernández-Ruiz, Agustín Álvarez-Marquina, Irene Hidalgo-delaGuía, Elena Garayzábal-Heinze, Nikola Hristov-Kalamov, Francisco Domínguez-Mateos, Cristina Conde, Rafael Martínez-Olalla
Format: Article
Language:English
Published: MDPI AG 2024-10-01
Series:Applied Sciences
Subjects:
CNN
deep learning
Smith–Magenis syndrome
speech
synthetic data
Online Access:https://www.mdpi.com/2076-3417/14/21/9747

Internet

https://www.mdpi.com/2076-3417/14/21/9747

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