Master's Thesis from the year 2013 in the subject Computer Science - Miscellaneous, grade: A+, University of Manchester, language: English, abstract: The aim of this project was to create a gender identification system that can be used to identify the gender of the speaker. In this dissertation I have explained the signal processing background such as Fourier transforms and DCT etc. that was needed to understand the underlying signal processing happening in digital devices. Apart from that I also investigated the different classification techniques such as Adaboost and Gaussian Mixture Models...

This book focuses on the basics of natural language processing and machine learning required to make a standard speech- based gender identification system. In this book all the required signal processing techniques required for understanding the basics of natural language processing including all types of Fourier transform, basic speech enhancement techniques, voice activity detection and pitch estimation using sub harmonic-to-harmonic ratio are briefly explained as well. In the machine learning part, all the relevant machine learning models like Support Vector Machines, Gaussian Mixture...