Different Performances of Machine Learning Models to Classify Dysphonic and Non-Dysphonic Voices.

Objective: To analyze the performance of 10 different machine learning (ML) classifiers for discrimination between dysphonic and non-dysphonic voices, using a variance threshold as a method for the selection and reduction of acoustic measurements used in the classifier.

Method: We analyzed 435 samples of individuals (337 female and 98 male), with a mean age of 41.07 ± 13.