Connectionist Speech Recognition
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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.
Connectionist Speech Recognition Status And Prospects
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Author : International Computer Science Institute
language : en
Publisher:
Release Date : 1991
Connectionist Speech Recognition Status And Prospects written by International Computer Science Institute and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991 with Speech recognition systems categories.
Abstract: "We report on recent advances in the ICSI connectionist speech recognition project. Highlights include: Experimental results showing that connectionist methods can improve the performance of a context independent maximum likelihood trained HMM system, resulting in a performance close to that achieved using state of the art context dependent HMM systems of much higher complexity. Mixing (context independent) connectionist probability estimates with maximum likelihood trained context dependent models to improve the performance of a state of the art system. The development of a network decomposition method that allows connectionist modelling of context dependent phones efficiently and parsimoniously, with no statistical independence assumptions."
Data Selection And Model Combination In Connectionist Speech Recognition
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Author : G. D. Cook
language : en
Publisher:
Release Date : 1997
Data Selection And Model Combination In Connectionist Speech Recognition written by G. D. Cook and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with categories.
Connectionism In Perspective
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Author : R. Pfeifer
language : en
Publisher: Elsevier
Release Date : 1989-08-23
Connectionism In Perspective written by R. Pfeifer and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 1989-08-23 with Computers categories.
An evaluation of the merits, potential, and limits of Connectionism, this book also illustrates current research programs and recent trends.Connectionism (also known as Neural Networks) is an exciting new field which has brought together researchers from different areas such as artificial intelligence, computer science, cognitive science, neuroscience, physics, and complex dynamics. These researchers are applying the connectionist paradigm in an interdisciplinary way to the analysis and design of intelligent systems.In this book, researchers from the above-mentioned fields not only report on their most recent research results, but also describe Connectionism from the perspective of their own field, looking at issues such as: - the effects and the utility of Connectionism for their field - the potential and limitations of Connectionism - can it be combined with other approaches?
Computational Models Of Speech Pattern Processing
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Author : Keith Ponting
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Computational Models Of Speech Pattern Processing written by Keith Ponting 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.
Proceedings of the NATO Advanced Study Institute on Computational Models of Speech Pattern Processing, held in St. Helier, Jersey, UK, July 7-18, 1997
Connectionist Speech Recognition
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Author : Martin Dickey
language : en
Publisher:
Release Date : 1988
Connectionist Speech Recognition written by Martin Dickey and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988 with Automatic speech recognition categories.
Connectionist Statistical And Symbolic Approaches To Learning For Natural Language Processing
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Author : Stefan Wermter
language : en
Publisher: Springer Science & Business Media
Release Date : 1996-03-15
Connectionist Statistical And Symbolic Approaches To Learning For Natural Language Processing written by Stefan Wermter 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 1996-03-15 with Computers categories.
This book is based on the workshop on New Approaches to Learning for Natural Language Processing, held in conjunction with the International Joint Conference on Artificial Intelligence, IJCAI'95, in Montreal, Canada in August 1995. Most of the 32 papers included in the book are revised selected workshop presentations; some papers were individually solicited from members of the workshop program committee to give the book an overall completeness. Also included, and written with the novice reader in mind, is a comprehensive introductory survey by the volume editors. The volume presents the state of the art in the most promising current approaches to learning for NLP and is thus compulsory reading for researchers in the field or for anyone applying the new techniques to challenging real-world NLP problems.
Connectionist Psychology
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Author : Rob Ellis
language : en
Publisher: Psychology Press
Release Date : 2020-02-25
Connectionist Psychology written by Rob Ellis and has been published by Psychology Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-25 with Psychology categories.
This textbook provides an introduction and review of connectionist models applied to psychological topics. Chapters include basic reviews of connectionist models, their properties and their attributes. The application of these models to the domains of perception, memory, attention, word processing, higher language processing, and cognitive neuropsychology is then reviewed.
Speech Processing Recognition And Artificial Neural Networks
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Author : Gerard Chollet
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Speech Processing Recognition And Artificial Neural Networks written by Gerard Chollet 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 Technology & Engineering categories.
Speech Processing, Recognition and Artificial Neural Networks contains papers from leading researchers and selected students, discussing the experiments, theories and perspectives of acoustic phonetics as well as the latest techniques in the field of spe ech science and technology. Topics covered in this book include; Fundamentals of Speech Analysis and Perceptron; Speech Processing; Stochastic Models for Speech; Auditory and Neural Network Models for Speech; Task-Oriented Applications of Automatic Speech Recognition and Synthesis.
Modeling Dynamics In Connectionist Speech Recognition The Time Index Model
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Author : International Computer Science Institute
language : en
Publisher:
Release Date : 1994
Modeling Dynamics In Connectionist Speech Recognition The Time Index Model written by International Computer Science Institute and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with Morgan, Nelson categories.
Abstract: "Here, we introduce an alternative to the Hidden Markov Model (HMM) as the underlying representation of speech production. HMMs suffer from well known limitations, such as the unrealistic assumption that the observations generated in a given state are independent and identically distributed (i.i.d). We propose a time index model that explicitly conditions the emission probability of a state on the time index, i.e., on the number of 'visits' in the current state of the Markov chain in a sequence. Thus, the proposed model does not require an i.i.d. assumption. The connectionist framework enables us to represent the dependence on the time index as a non-parametric distribution and to share parameters between different speech unit models. Furthermore, we discuss an extension to the basic time index model by incorporating information about the duration of the phone segments. Our initial results show that given the position of the boundaries between basic speech units, e.g., phones, we can improve our current connectionist system performance significantly by using this model. However, we still do not know whether these boundaries can be estimated reliably, nor do we know how much benefit we can obtain from this method given less accurate boundary information. Currently we are experimenting with two possible approaches: trying to learn smooth probability densities for the boundaries, and getting a set of reasonable segmentations from an N-Best search. In both cases we will need to consider the effect of incorrect boundaries, since they will undoubtedly occur."