Privacy-Preserving Machine Learning for Speech Processing (Paperback)

This thesis discusses the privacy issues in speech-based applications such as biometric authentication, surveillance, and external speech processing services. Author Manas A. Pathak presents solutions for privacy-preserving speech processing applications such as speaker verification, speaker identification and speech recognition. The author also introduces some of the tools from cryptography and machine learning and current techniques for improving the efficiency and scalability of the presented solutions. Experiments with prototype implementations of the solutions for execution time and accuracy on standardized speech datasets are also included in the text. Using the framework proposed may now make it possible for a surveillance agency to listen for a known terrorist without being able to hear conversation from non-targeted, innocent civilians.

General

Imprint:	Springer-Verlag New York
Country of origin:	United States
Series:	Springer Theses
Release date:	November 2014
First published:	2013
Authors:	Manas A. Pathak
Dimensions:	235 x 155 x 9mm (L x W x T)
Format:	Paperback
Pages:	142
ISBN-13:	978-1-4899-9120-1
Categories:	Books > Computing & IT > General theory of computing > Data structures Books > Computing & IT > Computer programming > Algorithms & procedures Books > Professional & Technical > Energy technology & engineering > Electrical engineering > General Books > Professional & Technical > Electronics & communications engineering > Communications engineering / telecommunications > General Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Applied optics > General Promotions
LSN:	1-4899-9120-4
Barcode:	9781489991201

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