Hidden Markov Models For Speech Recognition

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Hidden Markov Models Applications In Computer Vision

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Author : Horst Bunke
language : en
Publisher: World Scientific
Release Date : 2001-06-04

Hidden Markov Models Applications In Computer Vision written by Horst Bunke and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-06-04 with Computers categories.

Hidden Markov models (HMMs) originally emerged in the domain of speech recognition. In recent years, they have attracted growing interest in the area of computer vision as well. This book is a collection of articles on new developments in the theory of HMMs and their application in computer vision. It addresses topics such as handwriting recognition, shape recognition, face and gesture recognition, tracking, and image database retrieval.This book is also published as a special issue of the International Journal of Pattern Recognition and Artificial Intelligence (February 2001).

Hidden Markov Models For Speech Recognition

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Author : X. D. Huang
language : en
Publisher:
Release Date : 1990-01-01

Hidden Markov Models For Speech Recognition written by X. D. Huang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990-01-01 with Science categories.

Connectionist Speech Recognition

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Author : Hervé A. Bourlard
language : en
Publisher: Springer Science & Business Media
Release Date : 1994

Connectionist Speech Recognition written by Hervé A. Bourlard and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with Computers categories.

Connectionist Speech Recognition: A Hybrid Approach describes the theory and implementation of a method to incorporate neural network approaches into state of the art continuous speech recognition systems based on hidden Markov models (HMMs) to improve their performance. In this framework, neural networks (and in particular, multilayer perceptrons or MLPs) have been restricted to well-defined subtasks of the whole system, i.e. HMM emission probability estimation and feature extraction. The book describes a successful five-year international collaboration between the authors. The lessons learned form a case study that demonstrates how hybrid systems can be developed to combine neural networks with more traditional statistical approaches. The book illustrates both the advantages and limitations of neural networks in the framework of a statistical systems. Using standard databases and comparison with some conventional approaches, it is shown that MLP probability estimation can improve recognition performance. Other approaches are discussed, though there is no such unequivocal experimental result for these methods. Connectionist Speech Recognition is of use to anyone intending to use neural networks for speech recognition or within the framework provided by an existing successful statistical approach. This includes research and development groups working in the field of speech recognition, both with standard and neural network approaches, as well as other pattern recognition and/or neural network researchers. The book is also suitable as a text for advanced courses on neural networks or speech processing.

Automatic Speech Recognition

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Author : Dong Yu
language : en
Publisher: Springer
Release Date : 2014-11-11

Automatic Speech Recognition written by Dong Yu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-11 with Technology & Engineering categories.

This book provides a comprehensive overview of the recent advancement in the field of automatic speech recognition with a focus on deep learning models including deep neural networks and many of their variants. This is the first automatic speech recognition book dedicated to the deep learning approach. In addition to the rigorous mathematical treatment of the subject, the book also presents insights and theoretical foundation of a series of highly successful deep learning models.

Markov Models For Pattern Recognition

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Author : Gernot A. Fink
language : en
Publisher: Springer Science & Business Media
Release Date : 2014-01-14

Markov Models For Pattern Recognition written by Gernot A. Fink and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-14 with Computers categories.

This thoroughly revised and expanded new edition now includes a more detailed treatment of the EM algorithm, a description of an efficient approximate Viterbi-training procedure, a theoretical derivation of the perplexity measure and coverage of multi-pass decoding based on n-best search. Supporting the discussion of the theoretical foundations of Markov modeling, special emphasis is also placed on practical algorithmic solutions. Features: introduces the formal framework for Markov models; covers the robust handling of probability quantities; presents methods for the configuration of hidden Markov models for specific application areas; describes important methods for efficient processing of Markov models, and the adaptation of the models to different tasks; examines algorithms for searching within the complex solution spaces that result from the joint application of Markov chain and hidden Markov models; reviews key applications of Markov models.

Statistical Methods For Speech Recognition

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Author : Frederick Jelinek
language : en
Publisher: MIT Press
Release Date : 2022-11-01

Statistical Methods For Speech Recognition written by Frederick Jelinek and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-01 with Language Arts & Disciplines categories.

This book reflects decades of important research on the mathematical foundations of speech recognition. It focuses on underlying statistical techniques such as hidden Markov models, decision trees, the expectation-maximization algorithm, information theoretic goodness criteria, maximum entropy probability estimation, parameter and data clustering, and smoothing of probability distributions. The author's goal is to present these principles clearly in the simplest setting, to show the advantages of self-organization from real data, and to enable the reader to apply the techniques. Bradford Books imprint

The Application Of Hidden Markov Models In Speech Recognition

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Author : Mark Gales
language : en
Publisher: Now Publishers Inc
Release Date : 2008

The Application Of Hidden Markov Models In Speech Recognition written by Mark Gales and has been published by Now Publishers Inc this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Computers categories.

The Application of Hidden Markov Models in Speech Recognition presents the core architecture of a HMM-based LVCSR system and proceeds to describe the various refinements which are needed to achieve state-of-the-art performance.

Fundamentals In Handwriting Recognition

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Author : Sebastiano Impedovo
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Fundamentals In Handwriting Recognition written by Sebastiano Impedovo and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.

For many years researchers in the field of Handwriting Recognition were considered to be working in an area of minor importance in Pattern Recog nition. They had only the possibility to present the results of their research at general conferences such as the ICPR or publish their papers in journals such as some of the IEEE series or PR, together with many other papers generally oriented to the more promising areas of Pattern Recognition. The series of International Workshops on Frontiers in Handwriting Recog nition and International Conferences on Document Analysis and Recognition together with some special issues of several journals are now fulfilling the expectations of many researchers who have been attracted to this area and are involving many academic institutions and industrial companies. But in order to facilitate the introduction of young researchers into the field and give them both theoretically and practically powerful tools, it is now time that some high level teaching schools in handwriting recognition be held, also in order to unite the foundations of the field. Therefore it was my pleasure to organize the NATO Advanced Study Institute on Fundamentals in Handwriting Recognition that had its origin in many exchanges among the most important specialists in the field, during the International Workshops on Frontiers in Handwriting Recognition.

Hidden Markov Models And Dynamical Systems

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Author : Andrew M. Fraser
language : en
Publisher: SIAM
Release Date : 2008-01-01

Hidden Markov Models And Dynamical Systems written by Andrew M. Fraser and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-01-01 with Mathematics categories.

Presents algorithms for using HMMs and explains the derivation of those algorithms for the dynamical systems community.