LEADER 03501nam 2200469Ia 450 001 9910815937603321 005 20200520144314.0 010 $a1-60805-172-2 035 $a(CKB)3710000001409248 035 $a(MiAaPQ)EBC864230 035 $a(Au-PeEL)EBL864230 035 $a(CaPaEBR)ebr10457990 035 $a(OCoLC)726824636 035 $a(EXLCZ)993710000001409248 100 $a19911108d2011 uy 0 101 0 $aeng 135 $aurcn||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aRecent advances in robust speech recognition technology /$feditors, Javier Ramirez, Juan Manuel Gorriz 205 $a1st ed. 210 $a[S.l.] $cBentham Science Publishers$d[2011] 215 $a1 online resource (vi, 210 pages) $cillustrations 311 $a1-60805-389-X 320 $aIncludes bibliographical references and index. 327 $a02 Front_Back.pdf -- 03 eBooks End User License Agreement-Website -- 04 Content -- 05 Foreword -- 06 Preface -- 07 Contributors -- 08 Chapter1 -- 09 Chapter2 -- 09 Chapter2 -- 10 Chapter3 -- 11 chapter4 -- 12 Chapter5 -- 12 Chapter5 -- 13 Chapter6 -- 14 Chapter7 -- 15 Chapter8 -- 16 Chapter9 -- 17 Chapter10 -- 18 Chapter11 -- 19 Chapter12 -- 20 Chapter13 -- 21 Chapter14 -- 21 Chapter14 -- 22 index. 330 $aThis E-book is a collection of articles that describe advances in speech recognition technology. Robustness in speech recognition refers to the need to maintain high speech recognition accuracy even when the quality of the input speech is degraded, or when the acoustical, articulate, or phonetic characteristics of speech in the training and testing environments differ. Obstacles to robust recognition include acoustical degradations produced by additive noise, the effects of linear filtering, nonlinearities in transduction or transmission, as well as impulsive interfering sources, and diminished accuracy caused by changes in articulation produced by the presence of high-intensity noise sources. Although progress over the past decade has been impressive, there are significant obstacles to overcome before speech recognition systems can reach their full potential. Automatic speech recognition (ASR) systems must be robust to all levels, so that they can handle background or channel noise, the occurrence on unfamiliar words, new accents, new users, or unanticipated inputs. They must exhibit more ‘intelligence’ and integrate speech with other modalities, deriving the user’s intent by combining speech with facial expressions, eye movements, gestures, and other input features, and communicating back to the user through multimedia responses. Therefore, as speech recognition technology is transferred from the laboratory to the marketplace, robustness in recognition becomes increasingly significant. This E-book should be useful to computer engineers interested in recent developments in speech recognition technology. 606 $aSpeech processing systems 606 $aSpeech perception$xTechnological innovations 615 0$aSpeech processing systems. 615 0$aSpeech perception$xTechnological innovations. 676 $a006.4/54 701 $aRamirez$b Javier$01157447 701 $aGorriz$b Juan Manuel$01157445 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910815937603321 996 $aRecent advances in robust speech recognition technology$94083639 997 $aUNINA