Hearing loss classification via AlexNet and Support Vector Machine

Abstract

This paper presents a new method for detecting hearing loss. Our approach is first to use AlexNet to extract the features. Then, we use the Support Vector Machine as a classifier to classify the images. 10-fold cross-validation results showed that the sensitivities of the healthy control group, the left-sided hearing loss group, and the right-sided hearing loss group in this method were 94.67%, 94.00%, and 95.17%, respectively, achieving a very good effect compared with other hearing loss detection methods. In conclusion, our method is effective for the identification of hearing loss.