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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Privacy-Preserving Machine Learning for Speech Processing

Privacy-Preserving Machine Learning for Speech Processing

Pathak, Manas A.

Paperback

Series: Springer Theses

Technology & EngineeringGeneral Computers

ISBN10: 1489991204
ISBN13: 9781489991201
Publisher: Springer Nature
Published: Nov 9 2014
Pages: 142
Weight: 0.51
Height: 0.34 Width: 6.14 Depth: 9.21
Language: English
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.

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