Computer Models of Speech Using Fuzzy Algorithms

Computer Models of Speech Using Fuzzy Algorithms
Author: Renato de Mori
Publisher: Springer Science & Business Media
Total Pages: 505
Release: 2013-06-29
Genre: Science
ISBN: 1461337429

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.

Computational Auditory Scene Analysis

Computational Auditory Scene Analysis
Author: David F. Rosenthal
Publisher: CRC Press
Total Pages: 417
Release: 2021-02-01
Genre: Technology & Engineering
ISBN: 1000149323

The interest of AI in problems related to understanding sounds has a rich history dating back to the ARPA Speech Understanding Project in the 1970s. While a great deal has been learned from this and subsequent speech understanding research, the goal of building systems that can understand general acoustic signals--continuous speech and/or non-speech sounds--from unconstrained environments is still unrealized. Instead, there are now systems that understand "clean" speech well in relatively noiseless laboratory environments, but that break down in more realistic, noisier environments. As seen in the "cocktail-party effect," humans and other mammals have the ability to selectively attend to sound from a particular source, even when it is mixed with other sounds. Computers also need to be able to decide which parts of a mixed acoustic signal are relevant to a particular purpose--which part should be interpreted as speech, and which should be interpreted as a door closing, an air conditioner humming, or another person interrupting. Observations such as these have led a number of researchers to conclude that research on speech understanding and on nonspeech understanding need to be united within a more general framework. Researchers have also begun trying to understand computational auditory frameworks as parts of larger perception systems whose purpose is to give a computer integrated information about the real world. Inspiration for this work ranges from research on how different sensors can be integrated to models of how humans' auditory apparatus works in concert with vision, proprioception, etc. Representing some of the most advanced work on computers understanding speech, this collection of papers covers the work being done to integrate speech and nonspeech understanding in computer systems.

Pattern Analysis and Understanding

Pattern Analysis and Understanding
Author: Heinrich Niemann
Publisher: Springer Science & Business Media
Total Pages: 384
Release: 2013-04-17
Genre: Science
ISBN: 3642748996

In this second edition every chapter of the first edition of Pattern Analysis has been updated and expanded. The general view of a system for pattern analysis and understanding has remained unchanged, but many details have been revised. A short account of light and sound has been added to the introduction, some normalization techniques and a basic introduction to morphological operations have been added to the second chapter. Chapter 3 has been expanded significantly by topics like motion, depth, and shape from shading; additional material has also been added to the already existing sections of this chapter. The old sections of Chap. 4 have been reorganized, a general view of the classification problem has been added and material provided to incorporate techniques of word and object recognition and to give a short account of some types of neural nets. Almost no changes have been made in Chap. 5. The part on representation of control structures in Chap. 6 has been shortened, a section on the judgement of results has been added. Chapter 7 has been rewritten almost completely; the section on formal grammars has been reduced, the sections on production systems, semantic networks, and knowledge acquisition have been expanded, and sections on logic and explanation added. The old Chaps. 8 and 9 have been omitted. In summary, the new edition is a thorough revision and extensive update of the first one taking into account the progress in the field during recent years.

Syntactic and Structural Pattern Recognition

Syntactic and Structural Pattern Recognition
Author: Gabriel Ferrate
Publisher: Springer Science & Business Media
Total Pages: 456
Release: 2012-12-06
Genre: Computers
ISBN: 3642834620

Thirty years ago pattern recognition was dominated by the learning machine concept: that one could automate the process of going from the raw data to a classifier. The derivation of numerical features from the input image was not considered an important step. One could present all possible features to a program which in turn could find which ones would be useful for pattern recognition. In spite of significant improvements in statistical inference techniques, progress was slow. It became clear that feature derivation was a very complex process that could not be automated and that features could be symbolic as well as numerical. Furthennore the spatial relationship amongst features might be important. It appeared that pattern recognition might resemble language analysis since features could play the role of symbols strung together to form a word. This led. to the genesis of syntactic pattern recognition, pioneered in the middle and late 1960's by Russel Kirsch, Robert Ledley, Nararimhan, and Allan Shaw. However the thorough investigation of the area was left to King-Sun Fu and his students who, until his untimely death, produced most of the significant papers in this area. One of these papers (syntactic recognition of fingerprints) received the distinction of being selected as the best paper published that year in the IEEE Transaction on Computers. Therefore syntactic pattern recognition has a long history of active research and has been used in industrial applications.

Cognitive Radio Architecture

Cognitive Radio Architecture
Author: Joseph Mitola, III
Publisher: John Wiley & Sons
Total Pages: 486
Release: 2006-09-14
Genre: Technology & Engineering
ISBN: 0471742449

An exciting new technology, described by the one who invented it This is the first book dedicated to cognitive radio, a promising new technology that is poised to revolutionize the telecommunications industry with increased wireless flexibility. Cognitive radio technology integrates computational intelligence into software-defined radio for embedded intelligent agents that adapt to RF environments and user needs. Using this technology, users can more fully exploit the radio spectrum and services available from wireless connectivity. For example, an attempt to send a 10MB e-mail in a zone where carrier charges are high might cause a cognitive radio to alert its user and suggest waiting until getting to the office to use the LAN instead. Cognitive Radio Architecture examines an "ideal cognitive radio" that features autonomous machine learning, computer vision, and spoken or written language perception. The author of this exciting new book is the inventor of the technology and a leader in the field. Following his step-by-step introduction, readers can start building aware/adaptive radios and then make steps towards cognitive radio. After an introduction to adaptive, aware, and cognitive radio, the author develops three major themes in three sections: Foundations Radio Competence User Domain Competence The book makes the design principles of cognitive radio more accessible to students of teleinformatics, as well as to wireless communications systems developers. It therefore embraces the practice of cognitive radio as well as the theory. In particular, the publication develops a cognitive architecture that integrates disparate disciplines, including autonomous machine learning, computer vision, and language perception technologies. In addition, for the convenience of the reader, Web resources introducing key concepts such as speech applications programmer interfaces (APIs) are included. Although still five to ten years away from full deployment, telecommunications giants and research labs around the world are already dedicating R&D to this new technology. Telecommunications engineers as well as advanced undergraduate and graduate students can learn the promising possibilities of this innovative technology from the one who invented it.

Fuzzy Models and Algorithms for Pattern Recognition and Image Processing

Fuzzy Models and Algorithms for Pattern Recognition and Image Processing
Author: James C. Bezdek
Publisher: Springer Science & Business Media
Total Pages: 786
Release: 2006-09-28
Genre: Computers
ISBN: 0387245790

Fuzzy Models and Algorithms for Pattern Recognition and Image Processing presents a comprehensive introduction of the use of fuzzy models in pattern recognition and selected topics in image processing and computer vision. Unique to this volume in the Kluwer Handbooks of Fuzzy Sets Series is the fact that this book was written in its entirety by its four authors. A single notation, presentation style, and purpose are used throughout. The result is an extensive unified treatment of many fuzzy models for pattern recognition. The main topics are clustering and classifier design, with extensive material on feature analysis relational clustering, image processing and computer vision. Also included are numerous figures, images and numerical examples that illustrate the use of various models involving applications in medicine, character and word recognition, remote sensing, military image analysis, and industrial engineering.

Biomedical Signal Processing

Biomedical Signal Processing
Author: Arnon Cohen
Publisher: CRC Press
Total Pages: 210
Release: 2019-07-17
Genre: Science
ISBN: 1000694429

First published in 1986: The presentation of the material in the book follows the flow of events of the general signal processing system. After the signal has been acquired, some manipulations are applied in order to enhance the relevant information present in the signal. Simple, Optimal, and adaptive filtering are examples of such manipulations. The detection of wavelets is of importance in biomedical signals; they can be detected from the enhanced signal by several methods. The signal very often contains redundancies. When effective storing, transmission, or automatic classification are required, these redundancies have to be extracted.

Fuzzy Modelling

Fuzzy Modelling
Author: Witold Pedrycz
Publisher: Springer Science & Business Media
Total Pages: 399
Release: 2012-12-06
Genre: Mathematics
ISBN: 1461313651

Fuzzy Modelling: Paradigms and Practice provides an up-to-date and authoritative compendium of fuzzy models, identification algorithms and applications. Chapters in this book have been written by the leading scholars and researchers in their respective subject areas. Several of these chapters include both theoretical material and applications. The editor of this volume has organized and edited the chapters into a coherent and uniform framework. The objective of this book is to provide researchers and practitioners involved in the development of models for complex systems with an understanding of fuzzy modelling, and an appreciation of what makes these models unique. The chapters are organized into three major parts covering relational models, fuzzy neural networks and rule-based models. The material on relational models includes theory along with a large number of implemented case studies, including some on speech recognition, prediction, and ecological systems. The part on fuzzy neural networks covers some fundamentals, such as neurocomputing, fuzzy neurocomputing, etc., identifies the nature of the relationship that exists between fuzzy systems and neural networks, and includes extensive coverage of their architectures. The last part addresses the main design principles governing the development of rule-based models. Fuzzy Modelling: Paradigms and Practice provides a wealth of specific fuzzy modelling paradigms, algorithms and tools used in systems modelling. Also included is a panoply of case studies from various computer, engineering and science disciplines. This should be a primary reference work for researchers and practitioners developing models of complex systems.