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Produktbild: Automatic Speech and Speaker Recognition

Automatic Speech and Speaker Recognition Large Margin and Kernel Methods

155,99 €

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Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

01.03.2009

Herausgeber

Joseph Keshet + weitere

Verlag

John Wiley & Sons Inc

Seitenzahl

268

Maße (L/B/H)

24,9/17,3/2 cm

Gewicht

590 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-0-470-69683-5

Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

01.03.2009

Herausgeber

Verlag

John Wiley & Sons Inc

Seitenzahl

268

Maße (L/B/H)

24,9/17,3/2 cm

Gewicht

590 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-0-470-69683-5

Herstelleradresse

Libri GmbH
Europaallee 1
36244 Bad Hersfeld
DE

Email: gpsr@libri.de

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  • Produktbild: Automatic Speech and Speaker Recognition
  • List of Contributors.
     
    Preface.
     
    I Foundations.
     
    1 Introduction (Samy Bengio and Joseph Keshet).
     
    1.1 The Traditional Approach to Speech Processing.
     
    1.2 Potential Problems of the Probabilistic Approach.
     
    1.3 Support Vector Machines for Binary Classification.
     
    1.4 Outline.
     
    References.
     
    2 Theory and Practice of Support Vector Machines Optimization (Shai Shalev-Shwartz and Nathan Srebo).
     
    2.1 Introduction.
     
    2.2 SVM and L2-regularized Linear Prediction.
     
    2.3 Optimization Accuracy From a Machine Learning Perspective.
     
    2.4 Stochastic Gradient Descent.
     
    2.5 Dual Decomposition Methods.
     
    2.6 Summary.
     
    References.
     
    3 From Binary Classification to Categorial Prediction (Koby Crammer).
     
    3.1 Multi-category Problems.
     
    3.2 Hypothesis Class.
     
    3.3 Loss Functions.
     
    3.4 Hinge Loss Functions.
     
    3.5 A Generalized Perceptron Algorithm.
     
    3.6 A Generalized Passive-Aggressive Algorithm.
     
    3.7 A Batch Formulation.
     
    3.8 Concluding Remarks.
     
    3.9 Appendix. Derivations of the Duals of the Passive-Aggressive Algorithm and the Batch Formulation.
     
    References.
     
    II Acoustic Modeling.
     
    4 A Large Margin Algorithm for Forced Alignment (Joseph Keshet, Shai Shalev-Shwartz, Yoram Singer and Dan Chazan).
     
    4.1 Introduction.
     
    4.2 Problem Setting.
     
    4.3 Cost and Risk.
     
    4.4 A Large Margin Approach for Forced Alignment.
     
    4.5 An Iterative Algorithm.
     
    4.6 Efficient Evaluation of the Alignment Function.
     
    4.7 Base Alignment Functions.
     
    4.8 Experimental Results.
     
    4.9 Discussion.
     
    References.
     
    5 A Kernel Wrapper for Phoneme Sequence Recognition (Joseph Keshet and Dan Chazan).
     
    5.1 Introduction.
     
    5.2 Problem Setting.
     
    5.3 Frame-based Phoneme Classifier.
     
    5.4 Kernel-based Iterative Algorithm for Phoneme Recognition.
     
    5.5 Nonlinear Feature Functions.
     
    5.6 Preliminary Experimental Results.
     
    5.7 Discussion: Canwe Hope for Better Results?
     
    References.
     
    6 Augmented Statistical Models: Using Dynamic Kernels for Acoustic Models (Mark J. F. Gales).
     
    6.1 Introduction.
     
    6.2 Temporal Correlation Modeling.
     
    6.3 Dynamic Kernels.
     
    6.4 Augmented Statistical Models.
     
    6.5 Experimental Results.
     
    6.6 Conclusions.
     
    Acknowledgements.
     
    References.
     
    7 Large Margin Training of Continuous Density Hidden Markov Models (Fei Sha and Lawrence K. Saul).
     
    7.1 Introduction.
     
    7.2 Background.
     
    7.3 Large Margin Training.
     
    7.4 Experimental Results.
     
    7.5 Conclusion.
     
    References.
     
    III Language Modeling.
     
    8 A Survey of Discriminative Language Modeling Approaches for Large Vocabulary Continuous Speech Recognition (Brian Roark).
     
    8.1 Introduction.
     
    8.2 General Framework.
     
    8.3 Further Developments.
     
    8.4 Summary and Discussion.
     
    References.
     
    9 Large Margin Methods for Part-of-Speech Tagging (Yasemin Altun).
     
    9.1 Introduction.
     
    9.2 Modeling Sequence Labeling.
     
    9.3 Sequence Boosting.
     
    9.4 Hidden Markov Support Vector Machines.
     
    9.5 Experiments.
     
    9.6 Discussion.
     
    References.
     
    10 A Proposal for a Kernel Based Algorithm for Large Vocabulary Continuous Speech Recognition (Joseph Keshet).
     
    10.1 Introduction.
     
    10.2 Segment Models and Hidden Markov Models.