Privacy-Preserving Machine Learning for Speech Processing

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

שנה

2013

שפה

English

סדרה

Springer Theses, Recognizing Outstanding Ph.D. Research

הוצאה

Springer New York

מהדורות

3

עמודים

141

ISBN

9781461446392

מקור הנתונים: Wikidata