Repositori URV

Identificador: imarina:9262211

Handle: https://hdl.handle.net/20.500.11797/imarina9262211

Autores:
Morales Sanchez, DamianMoreno, AntonioJimenez Lopez, M. Dolores

Resumen:
Automatic gender detection has attracted the attention of many research fields such as forensic linguistics or marketing. Within these areas, gender detection has been approached as a classification problem and, for this reason, supervised Machine Learning algorithms such as Naive Bayes, Logistic Regression and Support Vector Machines, among others, have been employed. The latter algorithm has exhibited a better performance on gender detection. In recent years, with the development of Deep Learning methods, various neural networks structures such as Convolutional Neural Networks have been designed for gender detection. However, Deep Learning methods have led to a loss in the interpretability of the models. In this article, we review the AI techniques applied on gender detection.