Description

Book Synopsis
Presents the motivations for, intuitions behind, and basic mathematical models of natural spoken language communication. This book offers an overview of various 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.

Trade Review
"...a succinct presentation of the most important mathematical technology of speech technology and the author's ideas for overcoming the limitations of these techniques…" (Mathematical Reviews, 2005j)

Table of Contents
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

Mathematical Models for Speech Technology

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    £110.25

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    Order before 4pm today for delivery by Tue 30 Jun 2026.

    A Hardback by Stephen Levinson

    10 in stock


      View other formats and editions of Mathematical Models for Speech Technology by Stephen Levinson

      Publisher: John Wiley & Sons Inc
      Publication Date: 27/01/2005
      ISBN13: 9780470844076, 978-0470844076
      ISBN10: 0470844078

      Description

      Book Synopsis
      Presents the motivations for, intuitions behind, and basic mathematical models of natural spoken language communication. This book offers an overview of various 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.

      Trade Review
      "...a succinct presentation of the most important mathematical technology of speech technology and the author's ideas for overcoming the limitations of these techniques…" (Mathematical Reviews, 2005j)

      Table of Contents
      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

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