| 000 | 00000cam u22002058a 4500 | |
| 001 | 000045178640 | |
| 005 | 20250829143430 | |
| 008 | 041116s2005 enka b 001 0 eng | |
| 020 | ▼a 0470844078 (cloth) | |
| 040 | ▼a DLC ▼c DLC ▼d DLC ▼d 244002 ▼d 211009 | |
| 082 | 0 0 | ▼a 006.4/54/015118 ▼2 22 |
| 090 | ▼a 006.454 ▼b L665m | |
| 100 | 1 | ▼a Levinson, Stephen C., ▼d 1947- ▼0 AUTH(211009)22173. |
| 245 | 1 0 | ▼a Mathematical models for speech technology / ▼c Stephen E. Levinson. |
| 260 | ▼a Chichester : ▼b Wiley, ▼c c2005. | |
| 263 | ▼a 0501 | |
| 300 | ▼a xx, 261 p. : ▼b ill ; ▼c 26 cm. | |
| 504 | ▼a Includes bibliographical references and index. | |
| 650 | 0 | ▼a Speech processing systems. |
| 650 | 0 | ▼a Computational lingusitics. |
| 650 | 0 | ▼a Applied linguistics ▼x Mathematics. |
| 650 | 0 | ▼a Stochastic processes. |
| 650 | 0 | ▼a Knowledge, Theory of. |
소장정보
| No. | 소장처 | 청구기호 | 등록번호 | 도서상태 | 반납예정일 | 예약 | 서비스 |
|---|---|---|---|---|---|---|---|
| No. 1 | 소장처 과학도서관/Sci-Info(2층서고)/ | 청구기호 006.454 L665m | 등록번호 121117583 (4회 대출) | 도서상태 대출가능 | 반납예정일 | 예약 | 서비스 |
| No. 2 | 소장처 세종학술정보원/과학기술실(5층)/ | 청구기호 006.454 L665m | 등록번호 151179435 | 도서상태 대출가능 | 반납예정일 | 예약 | 서비스 |
| No. | 소장처 | 청구기호 | 등록번호 | 도서상태 | 반납예정일 | 예약 | 서비스 |
|---|---|---|---|---|---|---|---|
| No. 1 | 소장처 과학도서관/Sci-Info(2층서고)/ | 청구기호 006.454 L665m | 등록번호 121117583 (4회 대출) | 도서상태 대출가능 | 반납예정일 | 예약 | 서비스 |
| No. | 소장처 | 청구기호 | 등록번호 | 도서상태 | 반납예정일 | 예약 | 서비스 |
|---|---|---|---|---|---|---|---|
| No. 1 | 소장처 세종학술정보원/과학기술실(5층)/ | 청구기호 006.454 L665m | 등록번호 151179435 | 도서상태 대출가능 | 반납예정일 | 예약 | 서비스 |
컨텐츠정보
책소개
Mathematical Models of Spoken Language presents the motivations for, intuitions behind, and basic mathematical models of natural spoken language communication. A comprehensive overview is given of all aspects of the problem from the physics of speech production through the hierarchy of linguistic structure and ending with some observations on language and mind.
The author comprehensively explores the argument that these modern technologies are actually the most extensive compilations of linguistic knowledge available.Throughout the book, the emphasis is on placing all the material in a mathematically coherent and computationally tractable framework that captures linguistic structure.
It presents material that appears nowhere else and gives a unification of formalisms and perspectives used by linguists and engineers. Its unique features include a coherent nomenclature that emphasizes the deep connections amongst the diverse mathematical models and explores the methods by means of which they capture linguistic structure.
This contrasts with some of the superficial similarities described in the existing literature; the historical background and origins of the theories and models; the connections to related disciplines, e.g. artificial intelligence, automata theory and information theory; an elucidation of the current debates and their intellectual origins; many important little-known results and some original proofs of fundamental results, e.g. a geometric interpretation of parameter estimation techniques for stochastic models and finally the author's own unique perspectives on the future of this discipline.
There is a vast literature on Speech Recognition and Synthesis however, this book is unlike any other in the field. Although it appears to be a rapidly advancing field, the fundamentals have not changed in decades. Most of the results are presented in journals from which it is difficult to integrate and evaluate all of these recent ideas. Some of the fundamentals have been collected into textbooks, which give detailed descriptions of the techniques but no motivation or perspective. The linguistic texts are mostly descriptive and pictorial, lacking the mathematical and computational aspects. This book strikes a useful balance by covering a wide range of ideas in a common framework. It provides all the basic algorithms and computational techniques and an analysis and perspective, which allows one to intelligently read the latest literature and understand state-of-the-art techniques as they evolve.
New feature
Humans use language to convey meaningful messages to each other. Linguistic competence consists in the ability to express meaning reliably, not simply to obtain faithful lexical transcriptions. This invaluable reference tool is the product of many years' experience and research on language and speech technology. It presents the motivations for, intuitions behind and basic mathematical models of natural spoken language communication. From a preliminary discussion on the physics of speech production and the taxonomy of linguistic structure, there is a natural progression taking in issues of grammatical inference, automatic speech recognition and constructive theories of language. The author counterbalances theoretical explanations and illustrations with questions of a more philosophical nature designed to highlight the seemingly limitless future potential of speech technology.- Emphasizes the physics of speech production in an argument underpinned by mathematical models of linguistic structure.
- Collates the formalisms and perspectives used by linguists and engineers and examines established theories, including the Markov process, the Chomsky hierarchy, the Miller-Nicely experiments and Baum and Baker’s experiments.
- Contains strong sections on the current status and evolution of Artificial Intelligence, the problem of consciousness and future prospects for a science of the mind.
- Illustrates all points throughout using detailed real world examples.
정보제공 :
목차
Author's preface.
1 Introduction
2 Preliminaries
2.1 The physics of speech production
2.2 The source-filter model
2.3 Information-bearing features of the speech signal
2.4 Time-frequency representations
2.5 Classifications of acoustic patterns in speech
2.6 Temporal invariance and stationarity
2.7 Taxonomy of linguistic structure
3 Mathematical models of linguistic structure
3.1 Probabilistic functions of a discrete Markov process
3.2 Formal grammars and abstract automata
4 Syntactic analysis
4.1 Deterministic parsing algorithms
4.2 Probabilistic parsing algorithms
4.3 Parsing natural language
5 Grammatical inference
5.1 Exact inference and Gold's theorem
5.2 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
6.3 Recognition error rates and entropy
7 Automatic speech recognition and constructive theories of language
7.1 Integrated architectures
7.2 Modular architectures
7.3 Parameter estimation from fluent speech
7.4 System performance
7.5 Other speech technologies
8 Automatic speech understanding and semantics
8.1 Transcription and comprehension
8.2 Limited domain semantics
8.3 The semantics of natural language
8.4 System architectures
8.5 Human and machine performance
9 Theories of mind and language
9.1 The challenge of automatic natural language understanding
9.2 Metaphors for mind
9.3 The artificial intelligence program
10 A speculation on the prospects for a science of the mind
10.1 The parable of the thermos bottle: measurements and symbols
10.2 The four questions of science
10.3 A constructive theory of the mind
10.4 The problem of consciousness
10.5 The role of sensorimotor function, associative memory and reinforcement learning in automatic acquisition of spoken language by an autonomous robot
10.6 Final thoughts: predicting the course of discovery
정보제공 :