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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...
| Call Number: | Libro Electrónico |
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| Main Author: | |
| Corporate Author: | |
| Format: | Electronic eBook |
| Language: | Inglés |
| Published: |
New York, NY :
Springer New York : Imprint: Springer,
2013.
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| Edition: | 1st ed. 2013. |
| Series: | Springer Theses, Recognizing Outstanding Ph.D. Research,
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| Subjects: | |
| Online Access: | Texto Completo |
Table of Contents:
- Thesis Overview
- Speech Processing Background
- Privacy Background
- Overview of Speaker Verification with Privacy
- Privacy-Preserving Speaker Verification Using Gaussian Mixture Models
- Privacy-Preserving Speaker Verification as String Comparison
- Overview of Speaker Indentification with Privacy
- Privacy-Preserving Speaker Identification Using Gausian Mixture Models
- Privacy-Preserving Speaker Identification as String Comparison
- Overview of Speech Recognition with Privacy
- Privacy-Preserving Isolated-Word Recognition
- Thesis Conclusion
- Future Work
- Differentially Private Gaussian Mixture Models.