Computer Models of Speech Using Fuzzy Algorithms


Book Description

It is with great pleasure that I present this third volume of the series "Advanced Applications in Pattern Recognition." It represents the summary of many man- (and woman-) years of effort in the field of speech recognition by tne author's former team at the University of Turin. It combines the best results in fuzzy-set theory and artificial intelligence to point the way to definitive solutions to the speech-recognition problem. It is my hope that it will become a classic work in this field. I take this opportunity to extend my thanks and appreciation to Sy Marchand, Plenum's Senior Editor responsible for overseeing this series, and to Susan Lee and Jo Winton, who had the monumental task of preparing the camera-ready master sheets for publication. Morton Nadler General Editor vii PREFACE Si parva licet componere magnis Virgil, Georgics, 4,176 (37-30 B.C.) The work reported in this book results from years of research oriented toward the goal of making an experimental model capable of understanding spoken sentences of a natural language. This is, of course, a modest attempt compared to the complexity of the functions performed by the human brain. A method is introduced for conce1v1ng modules performing perceptual tasks and for combining them in a speech understanding system.




Readings in Fuzzy Sets for Intelligent Systems


Book Description

Readings in Fuzzy Sets for Intelligent Systems is a collection of readings that explore the main facets of fuzzy sets and possibility theory and their use in intelligent systems. Basic notions in fuzzy set theory are discussed, along with fuzzy control and approximate reasoning. Uncertainty and informativeness, information processing, and membership, cognition, neural networks, and learning are also considered. Comprised of eight chapters, this book begins with a historical background on fuzzy sets and possibility theory, citing some forerunners who discussed ideas or formal definitions very close to the basic notions introduced by Lotfi Zadeh (1978). The reader is then introduced to fundamental concepts in fuzzy set theory, including symmetric summation and the setting of fuzzy logic; uncertainty and informativeness; and fuzzy control. Subsequent chapters deal with approximate reasoning; information processing; decision and management sciences; and membership, cognition, neural networks, and learning. Numerical methods for fuzzy clustering are described, and adaptive inference in fuzzy knowledge networks is analyzed. This monograph will be of interest to both students and practitioners in the fields of computer science, information science, applied mathematics, and artificial intelligence.




Advances in Computers


Book Description

Advances in Computers




Applications of Evolutionary Computing


Book Description

Evolutionary computation (EC) techniques are e?cient nature-inspired pl- ning and optimization methods based on the principles of natural evolution and genetics. Due to their e?ciency and the simple underlying principles, these methods can be used for a large number of problems in the context of problem solving,optimization,andmachinelearning. Alargeandcontinuouslyincreasing number of researchers and practitioners make use of EC techniques in many - plication domains. The book at hand presents a careful selection of relevant EC applications combined with thorough examinations of techniques for a successful application of EC. The presented papers illustrate the current state of the art in the application of EC and should help and inspire researchers and practitioners to develop e?cient EC methods for design and problem solving. All papers in this book were presented during EvoWorkshops 2005, which was a varying collection of workshops on application-oriented aspects of EC. Since 1999, the format of the EvoWorkshops has proved to be very successful and well representative of the advances in the application of EC. Consequently, over the last few years, EvoWorkshops has become one of the major events addressing the application of EC. In contrast to other large conferences in the EC ?eld, the EvoWorkshops focus solely on application aspects of EC and are an important link between EC research and the application of EC in a large variety of di?erent domains.




Neural Fuzzy Control Systems With Structure And Parameter Learning


Book Description

A general neural-network-based connectionist model, called Fuzzy Neural Network (FNN), is proposed in this book for the realization of a fuzzy logic control and decision system. The FNN is a feedforward multi-layered network which integrates the basic elements and functions of a traditional fuzzy logic controller into a connectionist structure which has distributed learning abilities.In order to set up this proposed FNN, the author recommends two complementary structure/parameter learning algorithms: a two-phase hybrid learning algorithm and an on-line supervised structure/parameter learning algorithm.Both of these learning algorithms require exact supervised training data for learning. In some real-time applications, exact training data may be expensive or even impossible to get. To solve this reinforcement learning problem for real-world applications, a Reinforcement Fuzzy Neural Network (RFNN) is further proposed. Computer simulation examples are presented to illustrate the performance and applicability of the proposed FNN, RFNN and their associated learning algorithms for various applications.







Syntactic and Structural Pattern Recognition


Book Description

This book is currently the only one on this subject containing both introductory material and advanced recent research results. It presents, at one end, fundamental concepts and notations developed in syntactic and structural pattern recognition and at the other, reports on the current state of the art with respect to both methodology and applications. In particular, it includes artificial intelligence related techniques, which are likely to become very important in future pattern recognition.The book consists of individual chapters written by different authors. The chapters are grouped into broader subject areas like “Syntactic Representation and Parsing”, “Structural Representation and Matching”, “Learning”, etc. Each chapter is a self-contained presentation of one particular topic. In order to keep the original flavor of each contribution, no efforts were undertaken to unify the different chapters with respect to notation. Naturally, the self-containedness of the individual chapters results in some redundancy. However, we believe that this handicap is compensated by the fact that each contribution can be read individually without prior study of the preceding chapters. A unification of the spectrum of material covered by the individual chapters is provided by the subject and author index included at the end of the book.




Robustness in Automatic Speech Recognition


Book Description

Foreword Looking back the past 30 years. we have seen steady progress made in the area of speech science and technology. I still remember the excitement in the late seventies when Texas Instruments came up with a toy named "Speak-and-Spell" which was based on a VLSI chip containing the state-of-the-art linear prediction synthesizer. This caused a speech technology fever among the electronics industry. Particularly. applications of automatic speech recognition were rigorously attempt ed by many companies. some of which were start-ups founded just for this purpose. Unfortunately. it did not take long before they realized that automatic speech rec ognition technology was not mature enough to satisfy the need of customers. The fever gradually faded away. In the meantime. constant efforts have been made by many researchers and engi neers to improve the automatic speech recognition technology. Hardware capabilities have advanced impressively since that time. In the past few years. we have been witnessing and experiencing the advent of the "Information Revolution." What might be called the second surge of interest to com mercialize speech technology as a natural interface for man-machine communication began in much better shape than the first one. With computers much more powerful and faster. many applications look realistic this time. However. there are still tremendous practical issues to be overcome in order for speech to be truly the most natural interface between humans and machines.







Pattern Recognition Theory and Applications


Book Description

This book is the outcome of a NATO Advanced Study Institute on Pattern Recog nition Theory and Applications held in Spa-Balmoral, Belgium, in June 1986. This Institute was the third of a series which started in 1975 in Bandol, France, at the initia tive of Professors K. S. Fu and A. Whinston, and continued in 1981 in Oxford, UK, with Professors K. S. Fu, J. Kittler and L. -F. Pau as directors. As early as in 1981, plans were made to pursue the series in about 1986 and possibly in Belgium, with Professor K. S. Fu and the present editors as directors. Unfortunately, Ie sort en decida autrement: Professor Fu passed away in the spring of 1985. His sudden death was an irreparable loss to the scientific community and to all those who knew him as an inspiring colleague, a teacher or a dear friend. Soon after, Josef Kittler and I decided to pay a small tribute to his memory by helping some of his plans to materialize. With the support of the NATO Scientific Affairs Division, the Institute became a reality. It was therefore but natural that the proceedings of the Institute be dedicated to him. The book contains most of the papers that were presented at the Institute. Papers are grouped along major themes which hopefully represent the major areas of contem porary research. These are: 1. Statistical methods and clustering techniques 2. Probabilistic relaxation techniques 3. From Markovian to connectionist models 4.