LEADER 01279nam 2200385z- 450 001 9910689822803321 005 20161209104532.0 035 $a(CKB)5860000000024067 035 $a(BIP)012880464 035 $a(EXLCZ)995860000000024067 100 $a20220406c2005uuuu -u- - 101 0 $aeng 200 10$aFuture of the hydrogen fuel cell $ehearing before the Subcommittee on Science, Technology, and Space of the Committee on Commerce, Science, and Transportation, United States Senate, One Hundred Eighth Congress, first session, May 7, 2003 215 $a1 online resource (iii, 58 p.) $cill 311 $a0-16-074711-2 517 $aFuture of the hydrogen fuel cell 606 $aHydrogen as fuel 606 $aFuel cells 606 $aHydrogen cars$zUnited States 606 $aEnergy policy$zUnited States 610 $aHydrogen as fuel 610 $aFuel cells 610 $aHydrogen cars 610 $aEnergy policy 610 $aTechnology & engineering 610 $aPolitical science 615 0$aHydrogen as fuel. 615 0$aFuel cells. 615 0$aHydrogen cars 615 0$aEnergy policy 676 $a634.9/618 906 $aBOOK 912 $a9910689822803321 996 $aFuture of the hydrogen fuel cell$93193425 997 $aUNINA LEADER 03908nam 22007335 450 001 9910299851603321 005 20251010221309.0 010 $a1-4471-5779-6 024 7 $a10.1007/978-1-4471-5779-3 035 $a(CKB)3710000000280720 035 $a(EBL)1967878 035 $a(OCoLC)895161787 035 $a(SSID)ssj0001386203 035 $a(PQKBManifestationID)11896935 035 $a(PQKBTitleCode)TC0001386203 035 $a(PQKBWorkID)11350079 035 $a(PQKB)10870782 035 $a(DE-He213)978-1-4471-5779-3 035 $a(MiAaPQ)EBC1967878 035 $a(PPN)183096525 035 $a(EXLCZ)993710000000280720 100 $a20141111d2015 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aAutomatic Speech Recognition $eA Deep Learning Approach /$fby Dong Yu, Li Deng 205 $a1st ed. 2015. 210 1$aLondon :$cSpringer London :$cImprint: Springer,$d2015. 215 $a1 online resource (329 p.) 225 1 $aSignals and Communication Technology,$x1860-4862 300 $aDescription based upon print version of record. 311 08$a1-4471-5778-8 320 $aIncludes bibliographical references and index. 327 $aSection 1: Automatic speech recognition: Background -- Feature extraction: basic frontend -- Acoustic model: Gaussian mixture hidden Markov model -- Language model: stochastic N-gram -- Historical reviews of speech recognition research: 1st, 2nd, 3rd, 3.5th, and 4th generations -- Section 2: Advanced feature extraction and transformation -- Unsupervised feature extraction -- Discriminative feature transformation -- Section 3: Advanced acoustic modeling -- Conditional random field (CRF) and hidden conditional random field (HCRF) -- Deep-Structured CRF -- Semi-Markov conditional random field -- Deep stacking models -- Deep neural network ? hidden Markov hybrid model -- Section 4: Advanced language modeling -- Discriminative Language model -- Log-linear language model -- Neural network language model. 330 $aThis book provides a comprehensive overview of the recent advancement in the field of automatic speech recognition with a focus on deep learning models including deep neural networks and many of their variants. This is the first automatic speech recognition book dedicated to the deep learning approach. In addition to the rigorous mathematical treatment of the subject, the book also presents insights and theoretical foundation of a series of highly successful deep learning models. 410 0$aSignals and Communication Technology,$x1860-4862 606 $aSignal processing 606 $aImage processing 606 $aSpeech processing systems 606 $aAcoustical engineering 606 $aApplication software 606 $aSignal, Image and Speech Processing$3https://scigraph.springernature.com/ontologies/product-market-codes/T24051 606 $aEngineering Acoustics$3https://scigraph.springernature.com/ontologies/product-market-codes/T16000 606 $aComputer Appl. in Social and Behavioral Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/I23028 615 0$aSignal processing. 615 0$aImage processing. 615 0$aSpeech processing systems. 615 0$aAcoustical engineering. 615 0$aApplication software. 615 14$aSignal, Image and Speech Processing. 615 24$aEngineering Acoustics. 615 24$aComputer Appl. in Social and Behavioral Sciences. 676 $a006.454 700 $aYu$b Dong$4aut$4http://id.loc.gov/vocabulary/relators/aut$0466593 702 $aDeng$b Li$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910299851603321 996 $aAutomatic Speech Recognition$92540265 997 $aUNINA