Modelling Humanoid Robot Audition for Sound Source Localization Using Artifical Neural Network

This study presents a new method for computational auditory systems that models humanoid robot audition for determining the direction of a sound source and integrates it into the Arslan humanoid robot. It does this by employing artificial neural networks. With an emphasis on precision and flexibility, the study provides a workable answer for real-world applications. The encouraging outcomes confirm the system's approach's efficacy and its potential for practical uses. In order to get greater precision and flexibility in practical applications, the study also tackles some constraints. The outcomes show encouraging accuracy rates for a range of sample sizes, highlighting the suggested method's scalability and dependability.