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Privacy-Preserving Machine Learning for Speech Processing
Manas A. Pathak
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Description for Privacy-Preserving Machine Learning for Speech Processing
Hardback. Discusses the privacy issues in speech - based applications such as biometric authentication, surveillance, and external speech processing services. This title presents solutions for privacy - preserving speech processing applications such as speaker verification, speaker identification and speech recognition. Series: Springer Theses. Num Pages: 160 pages, 7 black & white tables, biography. BIC Classification: TJK; TTA; UYQM; UYQS. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 15. Weight in Grams: 409.
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 ... Read more
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 ... Read more
Product Details
Format
Hardback
Publication date
2012
Publisher
Springer-Verlag New York Inc. United States
Number of pages
160
Condition
New
Series
Springer Theses
Number of Pages
142
Place of Publication
New York, NY, United States
ISBN
9781461446385
SKU
V9781461446385
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
About Manas A. Pathak
Dr. Manas A. Pathak received the BTech degree in computer science from Visvesvaraya National Institute of Technology, Nagpur, India, in 2006, and the MS and PhD degrees from the Language Technologies Institute at Carnegie Mellon University (CMU) in 2009 and 2012 respectively. He is currently working as a research scientist at Adchemy, Inc. His research interests include intersection of data privacy, machine learning, ... Read more
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