Download or read book Connectionist Speech Recognition written by Hervé A. Bourlard and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Connectionist Speech Recognition written by Hervé A. Bourlard and published by Springer Science & Business Media. This book was released on 1994 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Connectionist Approaches To Clinical Problems in Speech and Language written by Raymond G. Daniloff and published by Psychology Press. This book was released on 2001-08-01 with total page 327 pages. Available in PDF, EPUB and Kindle. Book excerpt: Connectionist accounts of language acquisition, processing, and dissolution proliferate despite attacks from some linguists, cognitive scientists, and engineers. Although the networks of exquisitely interconnected perceptrons postulated by PDP theorists may not be anatomically homologous with actual brain anatomy, a growing body of research suggests that the posited network functions can support many human behaviors. This volume brings together contributors with a variety of backgrounds and perspectives to explore, for the first time, the clinical implications of whole-language connectionist models. Demonstrating that these models are powerful and have explained many phenomena of language acquisition, language therapy, and speech processing, especially at the engineering level, they focus specifically on applications of connectionist theory to delayed language, aphasia, phonological acquisition, and speech perception. Connectionist models, they conclude, offer a new interpretive framework for the discussion of information processing in humans and other animals that will be of great utility to all those who study language and seek to intervene in language disorders.
Download or read book Connectionist Natural Language Processing written by Noel Sharkey and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: Connection science is a new information-processing paradigm which attempts to imitate the architecture and process of the brain, and brings together researchers from disciplines as diverse as computer science, physics, psychology, philosophy, linguistics, biology, engineering, neuroscience and AI. Work in Connectionist Natural Language Processing (CNLP) is now expanding rapidly, yet much of the work is still only available in journals, some of them quite obscure. To make this research more accessible this book brings together an important and comprehensive set of articles from the journal CONNECTION SCIENCE which represent the state of the art in Connectionist natural language processing; from speech recognition to discourse comprehension. While it is quintessentially Connectionist, it also deals with hybrid systems, and will be of interest to both theoreticians as well as computer modellers. Range of topics covered: Connectionism and Cognitive Linguistics Motion, Chomsky's Government-binding Theory Syntactic Transformations on Distributed Representations Syntactic Neural Networks A Hybrid Symbolic/Connectionist Model for Understanding of Nouns Connectionism and Determinism in a Syntactic Parser Context Free Grammar Recognition Script Recognition with Hierarchical Feature Maps Attention Mechanisms in Language Script-Based Story Processing A Connectionist Account of Similarity in Vowel Harmony Learning Distributed Representations Connectionist Language Users Representation and Recognition of Temporal Patterns A Hybrid Model of Script Generation Networks that Learn about Phonological Features Pronunciation in Text-to-Speech Systems
Download or read book Connectionist Models Applied to Automatic Speech Recognition written by Yoshua Bengio and published by . This book was released on 1987 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Data Selection and Model Combination in Connectionist Speech Recognition written by G. D. Cook and published by . This book was released on 1997 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Connectionist Speech Recognition written by Martin Dickey and published by . This book was released on 1988 with total page 66 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Some Connectionist Models and Their Application to Automatic Speech Recognition written by Yoshua Bengio and published by . This book was released on 1990 with total page 31 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: "We attempt to apply some connectionist models to automatic speech recognition. To do so we first consider ways to take advantage of a-priori knowledge in the design of those models. For example we consider the influence on generalization of various preprocessing methods, of the output coding and supervision as well as the architectural design. Recurrent neural networks contain cycles that enable them to retain some information about their past history in order to better predict the next output given the current input. Hence we describe two learning algorithms for these networks, one for general architectures (but not local in time) and one for constrained architectures with self- loops only. Given the importance of cpu requirements for back-propagation algorithms, we discuss some simple methods that can greatly accelerate the convergence of gradient descent with the back-propagation algorithm. In particular we introduce an original technique that provides a different learning rate to different layers of a multi-layered sigmoid network. We then study an alternative type of networks based on Radial Basis Functions (local representation) that can be initialized very fast. We present in detail the results of several experiments with these networks on the recognition of phonemes for the TIMIT databases (speaker-independent, continuous speech database). We propose an acceleration scheme for Radial Basis Functions based on a fast search of the subset of active hidden units. After considering successful networks that combine gaussian units and sigmoid units in a network we propose a cognitively relevant model that combines both a local representation and and [sic] a distributed representation subnetworks to which correspond respectively a fast-learning and a slow-learning capability. This system is based on a reorganization phase during which the information about prototypes and outliers stored in the local subsystem is transferred to the distributed representation subsystem."
Download or read book Connectionist Speech Recognition Status and Prospects written by International Computer Science Institute and published by . This book was released on 1991 with total page 23 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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."
Download or read book Handbook of Neural Networks for Speech Processing written by Shigeru Katagiri and published by Artech House Publishers. This book was released on 2000 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt: Here are the comprehensive details on cutting edge technologies employing neural networks for speech recognition and speech processing in modern communications. Going far beyond the simple speech recognition technologies on the market today, this new book, written by and for speech and signal processing engineers in industry, R&D, and academia, takes you to the forefront of the hottest emergent neural net-based speech processing techniques.
Download or read book Speech Recognition and Understanding written by Pietro Laface and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 557 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book collects the contributions to the NATO Advanced Study Institute on "Speech Recognition and Understanding: Recent Advances, Trends and Applications", held in Cetraro, Italy, during the first two weeks of July 1990. This Institute focused on three topics that are considered of particular interest and rich of i'p.novation by researchers in the fields of speech recognition and understanding: Advances in Hidden Markov modeling, connectionist approaches to speech and language modeling, and linguistic processing including language and dialogue modeling. The purpose of any ASI is that of encouraging scientific communications between researchers of NATO countries through advanced tutorials and presentations: excellent tutorials were offered by invited speakers that present in this book 15 papers which sum marize or detail the topics covered in their lectures. The lectures were complemented by discussions, panel sections and by the presentation of related works carried on by some of the attending researchers: these presentations have been collected in 42 short contributions to the Proceedings. This volume, that the reader can find useful for an overview, although incomplete, of the state of the art in speech understanding, is divided into 6 Parts.
Download or read book Connectionist Models of Cognition and Perception II written by Howard Bowman and published by World Scientific. This book was released on 2004 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book collects together refereed versions of papers presented at the Eighth Neural Computation and Psychology Workshop (NCPW 8). NCPW is a well-established workshop series that brings together researchers from different disciplines, such as artificial intelligence, cognitive science, computer science, neurobiology, philosophy and psychology. The articles are centred on the theme of connectionist modelling of cognition and perceptionn. The proceedings have been selected for coverage in: . OCo Index to Scientific & Technical Proceedings- (ISTP- / ISI Proceedings). OCo Index to Scientific & Technical Proceedings (ISTP CDROM version / ISI Proceedings). OCo Index to Social Sciences & Humanities Proceedings- (ISSHP- / ISI Proceedings). OCo Index to Social Sciences & Humanities Proceedings (ISSHP CDROM version / ISI Proceedings). OCo CC Proceedings OCo Engineering & Physical Sciences. OCo CC Proceedings OCo Biomedical, Biological & Agricultural Sciences."
Download or read book Speech recognition using connectionist networks written by Raymond Langworthy Watrous and published by . This book was released on 1990 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Speech Recognition Using Connectionist Networks written by Raymond Langworthy Watrous III and published by . This book was released on 1988 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A Connectionist Framework for Continuous Speech Recognition written by Timothy David Harrison and published by . This book was released on 1988 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Modeling Dynamics in Connectionist Speech Recognition the Time Index Model written by International Computer Science Institute and published by . This book was released on 1994 with total page 17 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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."
Download or read book A Connectionist Approach to Speech Recognition written by Stephen Renals and published by . This book was released on 1987 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
