000			03380nam a22005537a 4500
001			sulb-eb0022060
003			BD-SySUS
005			20160413122220.0
007			cr nn 008mamaa
008			121026s2013 xxu| s |||| 0|eng d
020			_a9781461446392 _9978-1-4614-4639-2
024	7		_a10.1007/978-1-4614-4639-2 _2doi
050		4	_aTK5102.9
050		4	_aTA1637-1638
050		4	_aTK7882.S65
072		7	_aTTBM _2bicssc
072		7	_aUYS _2bicssc
072		7	_aTEC008000 _2bisacsh
072		7	_aCOM073000 _2bisacsh
082	0	4	_a621.382 _223
100	1		_aPathak, Manas A. _eauthor.
245	1	0	_aPrivacy-Preserving Machine Learning for Speech Processing _h[electronic resource] / _cby Manas A. Pathak.
264		1	_aNew York, NY : _bSpringer New York : _bImprint: Springer, _c2013.
300			_aXVIII, 142 p. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aSpringer Theses, Recognizing Outstanding Ph.D. Research, _x2190-5053
505	0		_aThesis 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.
520			_aThis 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.
650		0	_aEngineering.
650		0	_aData structures (Computer science).
650		0	_aElectrical engineering.
650		0	_aPower electronics.
650	1	4	_aEngineering.
650	2	4	_aSignal, Image and Speech Processing.
650	2	4	_aCommunications Engineering, Networks.
650	2	4	_aData Structures, Cryptology and Information Theory.
650	2	4	_aPower Electronics, Electrical Machines and Networks.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9781461446385
830		0	_aSpringer Theses, Recognizing Outstanding Ph.D. Research, _x2190-5053
856	4	0	_uhttp://dx.doi.org/10.1007/978-1-4614-4639-2
912			_aZDB-2-ENG
942			_2Dewey Decimal Classification _ceBooks
999			_c44152 _d44152