000			04037nam a22005535i 4500
001			978-1-4614-6489-1
003			DE-He213
005			20140220082825.0
007			cr nn 008mamaa
008			130228s2013 xxu| s |||| 0|eng d
020			_a9781461464891 _9978-1-4614-6489-1
024	7		_a10.1007/978-1-4614-6489-1 _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		_aMoyal, Ami. _eauthor.
245	1	0	_aPhonetic Search Methods for Large Speech Databases _h[electronic resource] / _cby Ami Moyal, Vered Aharonson, Ella Tetariy, Michal Gishri.
264		1	_aNew York, NY : _bSpringer New York : _bImprint: Springer, _c2013.
300			_aX, 53 p. 21 illus., 6 illus. in color. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aSpringerBriefs in Electrical and Computer Engineering, _x2191-8112
505	0		_aKeyword Spotting out of Continuous Speech -- Introduction -- Problem Formulation: KWS in Large Speech Databases -- Target Applications of Keyword Spotting -- Keyword Spotting Methods -- LVCSR-Based KWS -- Acoustic KWS -- Phonetic Search KWS -- Discussion: Why Phonetic Search? -- Response Time -- KWS Performance -- Keyword Flexibility -- Phonetic Search -- The Search Mechanism -- Using Phonetic Search for KWS -- Computational Complexity Analysis -- Search Space Complexity Reduction -- Overview -- Complexity Reduction in Phonetic Search -- Anchor-based Phonetic Search -- Evaluating Phonetic Search KWS -- Performance Metrics -- Evaluation Process -- Evaluation Databases -- Evaluation Results -- Exhaustive Search. - Textual Benchmark -- KWS on Speech -- Anchor-based Search -- Textual Benchmark -- Reduced Complexity KWS on Speech -- Multiple Thresholds -- Lessons Learned from the Evaluation -- Summary -- Glossary of Acronyms -- References.
520			_a“Phonetic Search Methods for Large Databases” focuses on Keyword Spotting (KWS) within large speech databases. The brief will begin by outlining the challenges associated with Keyword Spotting within large speech databases using dynamic keyword vocabularies. It will then continue by highlighting the various market segments in need of KWS solutions, as well as, the specific requirements of each market segment. The work also includes a detailed description of the complexity of the task and the different methods that are used, including the advantages and disadvantages of each method and an in-depth comparison. The main focus will be on the Phonetic Search method and its efficient implementation. This will include a literature review of the various methods used for the efficient implementation of Phonetic Search Keyword Spotting, with an emphasis on the authors’ own research which entails a comparative analysis of the Phonetic Search method which includes algorithmic details. This brief is useful for researchers and developers in academia and industry from the fields of speech processing and speech recognition, specifically Keyword Spotting.
650		0	_aEngineering.
650		0	_aTranslators (Computer programs).
650		0	_aComputational linguistics.
650	1	4	_aEngineering.
650	2	4	_aSignal, Image and Speech Processing.
650	2	4	_aLanguage Translation and Linguistics.
650	2	4	_aComputational Linguistics.
700	1		_aAharonson, Vered. _eauthor.
700	1		_aTetariy, Ella. _eauthor.
700	1		_aGishri, Michal. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9781461464884
830		0	_aSpringerBriefs in Electrical and Computer Engineering, _x2191-8112
856	4	0	_uhttp://dx.doi.org/10.1007/978-1-4614-6489-1
912			_aZDB-2-ENG
999			_c95683 _d95683