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Mathematical models for speech technology [[electronic resource] /] / Stephen E. Levinson
Mathematical models for speech technology [[electronic resource] /] / Stephen E. Levinson
Autore Levinson Stephen E
Pubbl/distr/stampa Chichester, West Sussex, England ; ; Hoboken, NJ, USA, : John Wiley, c2005
Descrizione fisica 1 online resource (283 p.)
Disciplina 006.4/54/015118
006.454015118
410.15118
Soggetto topico Speech processing systems
Computational linguistics
Applied linguistics - Mathematics
Stochastic processes
Knowledge, Theory of
Soggetto genere / forma Electronic books.
ISBN 1-280-27512-X
9786610275120
0-470-02091-1
0-470-02090-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Mathematical Models for Speech Technology; Contents; Preface; 1 Introduction; 1.1 Milestones in the history of speech technology; 1.2 Prospects for the future; 1.3 Technical synopsis; 2 Preliminaries; 2.1 The physics of speech production; 2.1.1 The human vocal apparatus; 2.1.2 Boundary conditions; 2.1.3 Non-stationarity; 2.1.4 Fluid dynamical effects; 2.2 The source-filter model; 2.3 Information-bearing features of the speech signal; 2.3.1 Fourier methods; 2.3.2 Linear prediction and the Webster equation; 2.4 Time-frequency representations; 2.5 Classification of acoustic patterns in speech
2.5.1 Statistical decision theory2.5.2 Estimation of class-conditional probability density functions; 2.5.3 Information-preserving transformations; 2.5.4 Unsupervised density estimation - quantization; 2.5.5 A note on connectionism; 2.6 Temporal invariance and stationarity; 2.6.1 A variational problem; 2.6.2 A solution by dynamic programming; 2.7 Taxonomy of linguistic structure; 2.7.1 Acoustic phonetics, phonology, and phonotactics; 2.7.2 Morphology and lexical structure; 2.7.3 Prosody, syntax, and semantics; 2.7.4 Pragmatics and dialog; 3 Mathematical models of linguistic structure
3.1 Probabilistic functions of a discrete Markov process3.1.1 The discrete observation hidden Markov model; 3.1.2 The continuous observation case; 3.1.3 The autoregressive observation case; 3.1.4 The semi-Markov process and correlated observations; 3.1.5 The non-stationary observation case; 3.1.6 Parameter estimation via the EM algorithm; 3.1.7 The Cave-Neuwirth and Poritz results; 3.2 Formal grammars and abstract automata; 3.2.1 The Chomsky hierarchy; 3.2.2 Stochastic grammars; 3.2.3 Equivalence of regular stochastic grammars and discrete HMMs; 3.2.4 Recognition of well-formed strings
3.2.5 Representation of phonology and syntax4 Syntactic analysis; 4.1 Deterministic parsing algorithms; 4.1.1 The Dijkstra algorithm for regular languages; 4.1.2 The Cocke-Kasami-Younger algorithm for context-free languages; 4.2 Probabilistic parsing algorithms; 4.2.1 Using the Baum algorithm to parse regular languages; 4.2.2 Dynamic programming methods; 4.2.3 Probabilistic Cocke-Kasami-Younger methods; 4.2.4 Asynchronous methods; 4.3 Parsing natural language; 4.3.1 The right-linear case; 4.3.2 The Markovian case; 4.3.3 The context-free case; 5 Grammatical Inference
5.1 Exact inference and Gold's theorem5.2 Baum's algorithm for regular grammars; 5.3 Event counting in parse trees; 5.4 Baker's algorithm for context-free grammars; 6 Information-theoretic analysis of speech communication; 6.1 The Miller et al. experiments; 6.2 Entropy of an information source; 6.2.1 Entropy of deterministic formal languages; 6.2.2 Entropy of languages generated by stochastic grammars; 6.2.3 Epsilon representations of deterministic languages; 6.3 Recognition error rates and entropy; 6.3.1 Analytic results derived from the Fano bound; 6.3.2 Experimental results
7 Automatic speech recognition and constructive theories of language
Record Nr. UNINA-9910143741503321
Levinson Stephen E  
Chichester, West Sussex, England ; ; Hoboken, NJ, USA, : John Wiley, c2005
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Mathematical models for speech technology [[electronic resource] /] / Stephen E. Levinson
Mathematical models for speech technology [[electronic resource] /] / Stephen E. Levinson
Autore Levinson Stephen E
Pubbl/distr/stampa Chichester, West Sussex, England ; ; Hoboken, NJ, USA, : John Wiley, c2005
Descrizione fisica 1 online resource (283 p.)
Disciplina 006.4/54/015118
006.454015118
410.15118
Soggetto topico Speech processing systems
Computational linguistics
Applied linguistics - Mathematics
Stochastic processes
Knowledge, Theory of
ISBN 1-280-27512-X
9786610275120
0-470-02091-1
0-470-02090-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Mathematical Models for Speech Technology; Contents; Preface; 1 Introduction; 1.1 Milestones in the history of speech technology; 1.2 Prospects for the future; 1.3 Technical synopsis; 2 Preliminaries; 2.1 The physics of speech production; 2.1.1 The human vocal apparatus; 2.1.2 Boundary conditions; 2.1.3 Non-stationarity; 2.1.4 Fluid dynamical effects; 2.2 The source-filter model; 2.3 Information-bearing features of the speech signal; 2.3.1 Fourier methods; 2.3.2 Linear prediction and the Webster equation; 2.4 Time-frequency representations; 2.5 Classification of acoustic patterns in speech
2.5.1 Statistical decision theory2.5.2 Estimation of class-conditional probability density functions; 2.5.3 Information-preserving transformations; 2.5.4 Unsupervised density estimation - quantization; 2.5.5 A note on connectionism; 2.6 Temporal invariance and stationarity; 2.6.1 A variational problem; 2.6.2 A solution by dynamic programming; 2.7 Taxonomy of linguistic structure; 2.7.1 Acoustic phonetics, phonology, and phonotactics; 2.7.2 Morphology and lexical structure; 2.7.3 Prosody, syntax, and semantics; 2.7.4 Pragmatics and dialog; 3 Mathematical models of linguistic structure
3.1 Probabilistic functions of a discrete Markov process3.1.1 The discrete observation hidden Markov model; 3.1.2 The continuous observation case; 3.1.3 The autoregressive observation case; 3.1.4 The semi-Markov process and correlated observations; 3.1.5 The non-stationary observation case; 3.1.6 Parameter estimation via the EM algorithm; 3.1.7 The Cave-Neuwirth and Poritz results; 3.2 Formal grammars and abstract automata; 3.2.1 The Chomsky hierarchy; 3.2.2 Stochastic grammars; 3.2.3 Equivalence of regular stochastic grammars and discrete HMMs; 3.2.4 Recognition of well-formed strings
3.2.5 Representation of phonology and syntax4 Syntactic analysis; 4.1 Deterministic parsing algorithms; 4.1.1 The Dijkstra algorithm for regular languages; 4.1.2 The Cocke-Kasami-Younger algorithm for context-free languages; 4.2 Probabilistic parsing algorithms; 4.2.1 Using the Baum algorithm to parse regular languages; 4.2.2 Dynamic programming methods; 4.2.3 Probabilistic Cocke-Kasami-Younger methods; 4.2.4 Asynchronous methods; 4.3 Parsing natural language; 4.3.1 The right-linear case; 4.3.2 The Markovian case; 4.3.3 The context-free case; 5 Grammatical Inference
5.1 Exact inference and Gold's theorem5.2 Baum's algorithm for regular grammars; 5.3 Event counting in parse trees; 5.4 Baker's algorithm for context-free grammars; 6 Information-theoretic analysis of speech communication; 6.1 The Miller et al. experiments; 6.2 Entropy of an information source; 6.2.1 Entropy of deterministic formal languages; 6.2.2 Entropy of languages generated by stochastic grammars; 6.2.3 Epsilon representations of deterministic languages; 6.3 Recognition error rates and entropy; 6.3.1 Analytic results derived from the Fano bound; 6.3.2 Experimental results
7 Automatic speech recognition and constructive theories of language
Record Nr. UNINA-9910830695403321
Levinson Stephen E  
Chichester, West Sussex, England ; ; Hoboken, NJ, USA, : John Wiley, c2005
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Mathematical models for speech technology / / Stephen E. Levinson
Mathematical models for speech technology / / Stephen E. Levinson
Autore Levinson Stephen E
Pubbl/distr/stampa Chichester, West Sussex, England ; ; Hoboken, NJ, USA, : John Wiley, c2005
Descrizione fisica 1 online resource (283 p.)
Disciplina 006.4/54/015118
Soggetto topico Speech processing systems
Computational linguistics
Applied linguistics - Mathematics
Stochastic processes
Knowledge, Theory of
ISBN 9786610275120
9781280275128
128027512X
9780470020913
0470020911
9780470020906
0470020903
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Mathematical Models for Speech Technology; Contents; Preface; 1 Introduction; 1.1 Milestones in the history of speech technology; 1.2 Prospects for the future; 1.3 Technical synopsis; 2 Preliminaries; 2.1 The physics of speech production; 2.1.1 The human vocal apparatus; 2.1.2 Boundary conditions; 2.1.3 Non-stationarity; 2.1.4 Fluid dynamical effects; 2.2 The source-filter model; 2.3 Information-bearing features of the speech signal; 2.3.1 Fourier methods; 2.3.2 Linear prediction and the Webster equation; 2.4 Time-frequency representations; 2.5 Classification of acoustic patterns in speech
2.5.1 Statistical decision theory2.5.2 Estimation of class-conditional probability density functions; 2.5.3 Information-preserving transformations; 2.5.4 Unsupervised density estimation - quantization; 2.5.5 A note on connectionism; 2.6 Temporal invariance and stationarity; 2.6.1 A variational problem; 2.6.2 A solution by dynamic programming; 2.7 Taxonomy of linguistic structure; 2.7.1 Acoustic phonetics, phonology, and phonotactics; 2.7.2 Morphology and lexical structure; 2.7.3 Prosody, syntax, and semantics; 2.7.4 Pragmatics and dialog; 3 Mathematical models of linguistic structure
3.1 Probabilistic functions of a discrete Markov process3.1.1 The discrete observation hidden Markov model; 3.1.2 The continuous observation case; 3.1.3 The autoregressive observation case; 3.1.4 The semi-Markov process and correlated observations; 3.1.5 The non-stationary observation case; 3.1.6 Parameter estimation via the EM algorithm; 3.1.7 The Cave-Neuwirth and Poritz results; 3.2 Formal grammars and abstract automata; 3.2.1 The Chomsky hierarchy; 3.2.2 Stochastic grammars; 3.2.3 Equivalence of regular stochastic grammars and discrete HMMs; 3.2.4 Recognition of well-formed strings
3.2.5 Representation of phonology and syntax4 Syntactic analysis; 4.1 Deterministic parsing algorithms; 4.1.1 The Dijkstra algorithm for regular languages; 4.1.2 The Cocke-Kasami-Younger algorithm for context-free languages; 4.2 Probabilistic parsing algorithms; 4.2.1 Using the Baum algorithm to parse regular languages; 4.2.2 Dynamic programming methods; 4.2.3 Probabilistic Cocke-Kasami-Younger methods; 4.2.4 Asynchronous methods; 4.3 Parsing natural language; 4.3.1 The right-linear case; 4.3.2 The Markovian case; 4.3.3 The context-free case; 5 Grammatical Inference
5.1 Exact inference and Gold's theorem5.2 Baum's algorithm for regular grammars; 5.3 Event counting in parse trees; 5.4 Baker's algorithm for context-free grammars; 6 Information-theoretic analysis of speech communication; 6.1 The Miller et al. experiments; 6.2 Entropy of an information source; 6.2.1 Entropy of deterministic formal languages; 6.2.2 Entropy of languages generated by stochastic grammars; 6.2.3 Epsilon representations of deterministic languages; 6.3 Recognition error rates and entropy; 6.3.1 Analytic results derived from the Fano bound; 6.3.2 Experimental results
7 Automatic speech recognition and constructive theories of language
Record Nr. UNINA-9911019863803321
Levinson Stephen E  
Chichester, West Sussex, England ; ; Hoboken, NJ, USA, : John Wiley, c2005
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui