Auto-correlation and Fisher Face Algorithm based gender recognition using Voice and facial images
S Sujana, Srikanth G, Uma S, Rahul M, M Ratnababu · 2024
This work focuses on classifying speakers' gender based on their voice and facial features. These systems are useful for a number of things, including marketing, healthcare, user authentication, security, and more. We incorporated it to achieve high accuracy because gender recognition using voice or face, as implemented in the Uni-modal (facial images, voice samples) framework, suffers from poor accuracy. utilized a person's biological and behavioural traits as an input in this instance. The goal is to use the Auto-correlation method to estimate the speaker's gender from a speech sample, and Fisher face algorithm to identify the speaker's gender from a picture of their face, and integration of the results to improve the gender classifier's accuracy. A database containing voice and visual samples of both male and female pupils has been taken into consideration.