MARC record from Internet Archive

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001 ocn171257507
003 OCoLC
005 20200511040430.0
008 070913s2007 caua ob 000 0 eng d
006 m o d
007 cr mn|||||||||
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020 $a159829105X$q(electronic bk.)
020 $a9781598291056$q(electronic bk.)
020 $a9781598294033
020 $a1598294032
020 $z1598291041
020 $z9781598291049
024 7 $a10.2200/S00048ED1V01Y200609SAP003$2doi
035 $a(OCoLC)171257507$z(OCoLC)456124427$z(OCoLC)785734298$z(OCoLC)785775997$z(OCoLC)958839610$z(OCoLC)987450891$z(OCoLC)1027292006$z(OCoLC)1044247333$z(OCoLC)1058213382$z(OCoLC)1059523994$z(OCoLC)1087274709
050 4 $aP325.5.D38$bB45 2007
055 3 $aP98$b.B455 2007
072 7 $aLAN$x009040$2bisacsh
082 04 $a401/.9$222
100 1 $aBellegarda, Jerome Rene,$d1961-
245 10 $aLatent semantic mapping :$bprinciples & applications /$cJerome R. Bellegarda.
250 $a1st ed.
260 $a[San Rafael, Calif.] :$bMorgan & Claypool Publishers,$c℗♭2007.
300 $a1 online resource (x, 101 pages)
336 $atext$btxt$2rdacontent
337 $acomputer$bc$2rdamedia
338 $aonline resource$bcr$2rdacarrier
490 1 $aSynthesis lectures on speech and audio processing ;$v#3
500 $aTitle from PDF title page (viewed Sept. 13, 2007).
504 $aIncludes bibliographical references (pages 89-100).
505 0 $aPrinciples -- Introduction -- Motivation -- From LSA to LSM -- Organization -- Latent semantic mapping -- Co-occurrence matrix -- Vector representation -- Interpretation -- LSM feature space -- Closeness measures -- LSM framework extension -- Salient characteristics -- Computational effort -- Off-line cost -- Online cost -- Possible shortcuts -- Probabilistic extensions -- Dual probability model -- Probabilistic latent semantic analysis -- Inherent limitations -- Applications -- Junk e-mail filtering -- Conventional approaches -- LSM-based filtering -- Performance -- Semantic classification -- Underlying issues -- Semantic inference -- Caveats -- Language modeling -- N-gram limitations -- MultiSpan language modeling -- Smoothing -- Pronunciation modeling -- Grapheme-to-phoneme conversion -- Pronunciation by latent analogy -- Speaker verification -- The task -- LSM-based speaker verification -- TTS unit selection -- Concatenative synthesis -- LSM-based unit selection -- LSM-based boundary training -- Perspectives -- Discussion -- Inherent tradeoffs -- General applicability -- Conclusion -- Summary -- Perspectives.
520 $aLatent semantic mapping (LSM) is a generalization of latent semantic analysis (LSA), a paradigm originally developed to capture hidden word patterns in a text document corpus. In information retrieval, LSA enables retrieval on the basis of conceptual content, instead of merely matching words between queries and documents. It operates under the assumption that there is some latent semantic structure in the data, which is partially obscured by the randomness of word choice with respect to retrieval. Algebraic and/or statistical techniques are brought to bear to estimate this structure and get rid of the obscuring "noise." This results in a parsimonious continuous parameter description of words and documents, which then replaces the original parameterization in indexing and retrieval. This approach exhibits three main characteristics: 1) discrete entities (words and documents) are mapped onto a continuous vector space; 2) this mapping is determined by global correlation patterns; and 3) dimensionality reduction is an integral part of the process. Such fairly generic properties are advantageous in a variety of different contexts, which motivates a broader interpretation of the underlying paradigm. The outcome (LSM) is a data-driven framework for modeling meaningful global relationships implicit in large volumes of (not necessarily textual) data. This monograph gives a general overview of the framework, and underscores the multifaceted benefits it can bring to a number of problems in natural language understanding and spoken language processing. It concludes with a discussion of the inherent tradeoffs associated with the approach, and some perspectives on its general applicability to data-driven information extraction.
588 0 $aPrint version record.
546 $aEnglish.
650 0 $aLatent semantic indexing.
650 0 $aSemantics$xData processing.
650 0 $aSemantics$xMathematical models.
650 0 $aComputational linguistics.
650 0 $aAutomatic speech recognition.
650 7 $aLANGUAGE ARTS & DISCIPLINES$xLinguistics$xPsycholinguistics.$2bisacsh
650 7 $aAutomatic speech recognition.$2fast$0(OCoLC)fst00822769
650 7 $aComputational linguistics.$2fast$0(OCoLC)fst00871998
650 7 $aLatent semantic indexing.$2fast$0(OCoLC)fst01741896
650 7 $aSemantics$xData processing.$2fast$0(OCoLC)fst01112080
650 7 $aSemantics$xMathematical models.$2fast$0(OCoLC)fst01112082
655 0 $aElectronic books.
655 4 $aElectronic books.
776 08 $iPrint version:$z9781598291049
830 0 $aSynthesis lectures on speech and audio processing (Online) ;$v#3.
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856 40 $3Morgan & Claypool$uhttp://www.morganclaypool.com/doi/pdf/10.2200/S00048ED1V01Y200609SAP003
856 40 $3Morgan & Claypool$uhttps://doi.org/10.2200/S00048ED1V01Y200609SAP003
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856 40 $uhttp://www.library.yorku.ca/eresolver/?id=1064989
856 42 $3Morgan & Claypool$uhttp://www.morganclaypool.com/doi/abs/10.2200/S00048ED1V01Y200609SAP003
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