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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 identificat...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
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| Formato: | Electrónico eBook |
| Idioma: | Inglés |
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New York, NY :
Springer New York : Imprint: Springer,
2013.
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| Edición: | 1st ed. 2013. |
| Colección: | Springer Theses, Recognizing Outstanding Ph.D. Research,
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| Acceso en línea: | Texto Completo |
| Sumario: | 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. 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. |
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| Descripción Física: | XVIII, 142 p. online resource. |
| ISBN: | 9781461446392 |
| ISSN: | 2190-5061 |