Mathematical Models for Speech Technology

ISBN-10: 0470844078
ISBN-13: 9780470844076
Edition: 2005
Authors: Stephen Levinson
List price: $170.00
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Description: Speech and language technology is very high profile, with a growing interest in advancing it. This book addresses the increasing number of challenges facing sophisticated applications of human/computer communication.

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Book details

List price: $170.00
Copyright year: 2005
Publisher: John Wiley & Sons, Incorporated
Publication date: 3/4/2005
Binding: Hardcover
Pages: 282
Size: 7.00" wide x 10.00" long x 0.75" tall
Weight: 1.496
Language: English

Speech and language technology is very high profile, with a growing interest in advancing it. This book addresses the increasing number of challenges facing sophisticated applications of human/computer communication.

Preface
Introduction
Milestones in the history of speech technology
Prospects for the future
Technical synopsis
Preliminaries
The physics of speech production
The human vocal apparatus
Boundary conditions
Non-stationarity
Fluid dynamical effects
The source-filter model
Information-bearing features of the speech signal
Fourier methods
Linear prediction and the Webster equation
Time-frequency representations
Classification of acoustic patterns in speech
Statistical decision theory
Estimation of class-conditional probability density functions
Information-preserving transformations
Unsupervised density estimation - quantization
A note on connectionism
Temporal invariance and stationarity
A variational problem
A solution by dynamic programming
Taxonomy of linguistic structure
Acoustic phonetics, phonology, and phonotactics
Morphology and lexical structure
Prosody, syntax, and semantics
Pragmatics and dialog
Mathematical models of linguistic structure
Probabilistic functions of a discrete Markov process
The discrete observation hidden Markov model
The continuous observation case
The autoregressive observation case
The semi-Markov process and correlated observations
The non-stationary observation case
Parameter estimation via the EM algorithm
The Cave-Neuwirth and Poritz results
Formal grammars and abstract automata
The Chomsky hierarchy
Stochastic grammars
Equivalence of regular stochastic grammars and discrete HMMs
Recognition of well-formed strings
Representation of phonology and syntax
Syntactic analysis
Deterministic parsing algorithms
The Dijkstra algorithm for regular languages
The Cocke-Kasami-Younger algorithm for context-free languages
Probabilistic parsing algorithms
Using the Baum algorithm to parse regular languages
Dynamic programming methods
Probabilistic Cocke-Kasami-Younger methods
Asynchronous methods
Parsing natural language
The right-linear case
The Markovian case
The context-free case
Grammatical Inference
Exact inference and Gold's theorem
Baum's algorithm for regular grammars
Event counting in parse trees
Baker's algorithm for context-free grammars
Information-theoretic analysis of speech communication
The Miller et al. experiments
Entropy of an information source
Entropy of deterministic formal languages
Entropy of languages generated by stochastic grammars
Epsilon representations of deterministic languages
Recognition error rates and entropy
Analytic results derived from the Fano bound
Experimental results
Automatic speech recognition and constructive theories of language
Integrated architectures
Modular architectures
Acoustic-phonetic transcription
Lexical access
Syntax analysis
Parameter estimation from fluent speech
Use of the Baum algorithm
The role of text analysis
System performance
Other speech technologies
Articulatory speech synthesis
Very low-bandwidth speech coding
Automatic language identification
Automatic language translation
Automatic speech understanding and semantics
Transcription and comprehension
Limited domain semantics
A semantic interpreter
Error recovery
The semantics of natural language
Shallow semantics and mutual information
Graphical methods
Formal logical models of semantics
Relationship between syntax and semantics
System architectures
Human and machine performance
Theories of mind and language
The challenge of automatic natural language understanding
Metaphors for mind
Wiener's cybernetics and the diachronic history
The crisis in the foundations of mathematics
Turing's universal machine
The Church-Turing hypothesis
The artificial intelligence program
Functional equivalence and the strong theory of AI
The broken promise
Schorske's causes of cultural decline
The ahistorical blind alley
Observation, introspection and divine inspiration
Resurrecting the program by unifying the synchronic and diachronic
A Speculation on the prospects for a science of mind
The parable of the thermos bottle: measurements and symbols
The four questions of science
Reductionism and emergence
From early intuition to quantitative reasoning
Objections to mathematical realism
The objection from the diversity of the sciences
The objection from Cartesian duality
The objection from either free will or determinism
The postmodern objection
Beginning the new science
A constructive theory of mind
Reinterpreting the strong theory of AI
Generalizing the Turing test
The problem of consciousness
The role of sensorimotor function, associative memory and reinforcement learning in automatic acquisition of spoken language by an autonomous robot
Embodied mind from integrated sensorimotor function
Associative memory as the basis for thought
Reinforcement learning via interaction with physical reality
Semantics as sensorimotor memory
The primacy of semantics in linguistic structure
Thought as linguistic manipulation of mental representations of reality
Illy the autonomous robot
Software
Associative memory architecture
Performance
Obstacles to the program
Final thoughts: predicting the course of discovery
Bibliography
Index

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