most citedAutomatic Detection of Depression in Speech Using Ensemble Convolutional Neural Networks

131 citations · 212 across the 4 of their papers we have counts for

collaborators

5 papers

cs.SD2026

Elastic Net Regularization and Gabor Dictionary for Classification of Heart Sound Signals using Deep Learning

Mahmoud Fakhry, Ascensión Gallardo-Antolín

In this article, we propose the optimization of the resolution of time-frequency atoms and the regularization of fitting models to obtain better representations of heart sound sign…

eess.AS202417 cited

On combining acoustic and modulation spectrograms in an attention LSTM-based system for speech intelligibility level classification

Ascensión Gallardo-Antolín, Juan M. Montero

Speech intelligibility can be affected by multiple factors, such as noisy environments, channel distortions or physiological issues. In this work, we deal with the problem of autom…

eess.AS202448 cited

An Attention Long Short-Term Memory based system for automatic classification of speech intelligibility

Miguel Fernández-Díaz, Ascensión Gallardo-Antolín

Speech intelligibility can be degraded due to multiple factors, such as noisy environments, technical difficulties or biological conditions. This work is focused on the development…

eess.AS2024131 cited

Automatic Detection of Depression in Speech Using Ensemble Convolutional Neural Networks

Adrián Vázquez-Romero, Ascensión Gallardo-Antolín

This paper proposes a speech-based method for automatic depression classification. The system is based on ensemble learning for Convolutional Neural Networks (CNNs) and is evaluate…

eess.AS202416 cited

Enhancement of a Text-Independent Speaker Verification System by using Feature Combination and Parallel-Structure Classifiers

Kerlos Atia Abdalmalak, Ascensión Gallardo-Antol'in

Speaker Verification (SV) systems involve mainly two individual stages: feature extraction and classification. In this paper, we explore these two modules with the aim of improving…