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Automatic Speech and Speaker Recognition
Research in the field of automatic speech and speaker recognition has made a number of significant advances in the last two decades, influenced by advances in signal processing, algorithms, architectures, and hardware. These advances include: the adoption of a statistical pattern recognition paradigm; the use of the hidden Markov modeling framework to characterize both the spectral and the temporal variations in the speech signal; the use of a large set of speech utterance examples from a large population of speakers to train the hidden Markov models of some fundamental speech units; the organization of speech and language knowledge sources into a structural finite state network; and the use...
Modern Methods of Speech Processing
The term speech processing refers to the scientific discipline concerned with the analysis and processing of speech signals for getting the best benefit in various practical scenarios. These different practical scenarios correspond to a large variety of applications of speech processing research. Examples of some applications include enhancement, coding, synthesis, recognition and speaker recognition. A very rapid growth, particularly during the past ten years, has resulted due to the efforts of many leading scientists. The ideal aim is to develop algorithms for a certain task that maximize performance, are computationally feasible and are robust to a wide class of conditions. The purpose of...
Statistical Methods for Speech Recognition
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
System Modelling and Optimization
This conference, organized jointly by UTC and INRIA, is the biennial general conference of the IFIP Technical Committee 7 (System Modelling and Optimization), and reflects the activity of its members and working groups. These proceedings contain a collection of papers (82 from the more than 400 submitted) as well as the plenary lectures presented at the conference.
Computer Vision--ECCV '92
This volume collects the papers accepted for presentation at the Second European Conference on Computer Vision, held in Santa Margherita Ligure, Italy, May 19-22, 1992. Sixteen long papers, 41 short papers and 48 posters were selected from 308 submissions. The contributions are structured into 14 sections reflecting the major research topics in computer vision currently investigated worldwide. The sections are entitled: features, color, calibration and matching, depth, stereo-motion, tracking, active vision, binocular heads, curved surfaces and objects, reconstruction and shape, recognition, and applications.
Applied Parallel Computing. Advanced Scientific Computing
TheseproceedingscontainthepaperspresentedatPARA2002,theSixth- ternationalConferenceonAppliedParallelComputing. PARA2002washeldin Espoo,Finland,June15–18,2002,andhostedbyCSC,theFinnishinformation technologycenterforscience. Thegeneralthemeoftheconferencewasadvanced scienti?ccomputing. Theconferencedemonstratedtheabilityofadvancedscienti?ccomputingto solvereal-worldproblems,andhighlightedmethods,instruments,andtrendsin futurescienti?ccomputing. Theconferencebeganwithaone-daytutorialsession onGridprogramming. Theconferencefocusedonanapplication-oriented,multi-disciplinary,and multi-scaleapproach. Awidevarietyofscienti?ccomputingapplicationswere introduced,fromsemiconductorprocessingandbehaviorofthehumanbodyto oceanicandatmosphericphenomena. Scienti?ccomputingcoupledwithmulti-disciplinaryandmulti-scaleexp- tisewillplayasigni?cantroleinsolvingchallengingproblemsinscience.
Pattern Recognition in Speech and Language Processing
Over the last 20 years, approaches to designing speech and language processing algorithms have moved from methods based on linguistics and speech science to data-driven pattern recognition techniques. These techniques have been the focus of intense, fast-moving research and have contributed to significant advances in this field. Pattern Reco
TV Content Analysis
The rapid advancement of digital multimedia technologies has not only revolutionized the production and distribution of audiovisual content, but also created the need to efficiently analyze TV programs to enable applications for content managers and consumers. Leaving no stone unturned, TV Content Analysis: Techniques and Applications provides a de
Parallel Processing for Artificial Intelligence 2
With the increasing availability of parallel machines and the raising of interest in large scale and real world applications, research on parallel processing for Artificial Intelligence (AI) is gaining greater importance in the computer science environment. Many applications have been implemented and delivered but the field is still considered to be in its infancy.This book assembles diverse aspects of research in the area, providing an overview of the current state of technology. It also aims to promote further growth across the discipline. Contributions have been grouped according to their subject: architectures (3 papers), languages (4 papers), general algorithms (6 papers), and applicati...
