A Comprehensive Review of Machine Learning Techniques for Voice-Based Gender Recognition
Nandita, Bhawna Bhutoria Jain · 2023
For humans, determining a person’s gender by looking at a few traits is not difficult. This does not, however, apply to machines. To do this, machines must be trained. The process of analyzing speech data to detect a speaker’s gender is known as gender recognition by voice. There are several uses for gender recognition in the real world, including enhancing human-machine communication. For instance, the advertising might be tailored based on the gender and age of the caller. In criminal instances, it can also assist in the spotting of the accused, or at the very minimum, it can lessen the number of accused. This work presents a review concerning methods that use data from pitch and frequency of voice. We have described the difficulties encountered and examined the typical implementations of these approaches. The results show that data sets collected in controlled situations have shown good performance, but there is still much that can be done to increase the gender recognition system’s robustness in real-world settings.