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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
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 Models and Adaptive boosting are explained. Lastly the results of different gender identification systems that were implemented using state of the art techniques are portrait and analysed.
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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
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 Models and Adaptive boosting are explained. Lastly the results of different gender identification systems that were implemented using state of the art techniques are portrait and analysed.