96 research outputs found

    Spoken content retrieval: A survey of techniques and technologies

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    Speech media, that is, digital audio and video containing spoken content, has blossomed in recent years. Large collections are accruing on the Internet as well as in private and enterprise settings. This growth has motivated extensive research on techniques and technologies that facilitate reliable indexing and retrieval. Spoken content retrieval (SCR) requires the combination of audio and speech processing technologies with methods from information retrieval (IR). SCR research initially investigated planned speech structured in document-like units, but has subsequently shifted focus to more informal spoken content produced spontaneously, outside of the studio and in conversational settings. This survey provides an overview of the field of SCR encompassing component technologies, the relationship of SCR to text IR and automatic speech recognition and user interaction issues. It is aimed at researchers with backgrounds in speech technology or IR who are seeking deeper insight on how these fields are integrated to support research and development, thus addressing the core challenges of SCR

    CLiFF Notes: Research In Natural Language Processing at the University of Pennsylvania

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    The Computational Linguistics Feedback Forum (CLIFF) is a group of students and faculty who gather once a week to discuss the members\u27 current research. As the word feedback suggests, the group\u27s purpose is the sharing of ideas. The group also promotes interdisciplinary contacts between researchers who share an interest in Cognitive Science. There is no single theme describing the research in Natural Language Processing at Penn. There is work done in CCG, Tree adjoining grammars, intonation, statistical methods, plan inference, instruction understanding, incremental interpretation, language acquisition, syntactic parsing, causal reasoning, free word order languages, ... and many other areas. With this in mind, rather than trying to summarize the varied work currently underway here at Penn, we suggest reading the following abstracts to see how the students and faculty themselves describe their work. Their abstracts illustrate the diversity of interests among the researchers, explain the areas of common interest, and describe some very interesting work in Cognitive Science. This report is a collection of abstracts from both faculty and graduate students in Computer Science, Psychology and Linguistics. We pride ourselves on the close working relations between these groups, as we believe that the communication among the different departments and the ongoing inter-departmental research not only improves the quality of our work, but makes much of that work possible

    Aspekte der Charakterisierung phonologischer Sprachstörungen vs. verzögerter Spracherwerb bei jordanischem Arabisch sprechenden Kindern

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    Bader S'da SI. Issues in the characterisation of phonological speech impairment vs. delayed acquisition in Jordanian Arabic-Speaking children. Bielefeld (Germany): Bielefeld University; 2010.Eine Studie des Spracherwerbs des jordanischen Arabisch bei jungen Muttersprachlern.A study with children speaking or acquiring Jordanian Arabic with or without phonological impairments

    CLiFF Notes: Research in the Language Information and Computation Laboratory of The University of Pennsylvania

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    This report takes its name from the Computational Linguistics Feedback Forum (CLIFF), an informal discussion group for students and faculty. However the scope of the research covered in this report is broader than the title might suggest; this is the yearly report of the LINC Lab, the Language, Information and Computation Laboratory of the University of Pennsylvania. It may at first be hard to see the threads that bind together the work presented here, work by faculty, graduate students and postdocs in the Computer Science, Psychology, and Linguistics Departments, and the Institute for Research in Cognitive Science. It includes prototypical Natural Language fields such as: Combinatorial Categorial Grammars, Tree Adjoining Grammars, syntactic parsing and the syntax-semantics interface; but it extends to statistical methods, plan inference, instruction understanding, intonation, causal reasoning, free word order languages, geometric reasoning, medical informatics, connectionism, and language acquisition. With 48 individual contributors and six projects represented, this is the largest LINC Lab collection to date, and the most diverse

    Applied and Computational Linguistics

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    Розглядається сучасний стан прикладної та комп’ютерної лінгвістики, проаналізовано лінгвістичні теорії 20-го – початку 21-го століть під кутом розмежування різних аспектів мови з метою формалізованого опису у електронних лінгвістичних ресурсах. Запропоновано критичний огляд таких актуальних проблем прикладної (комп’ютерної) лінгвістики як укладання комп’ютерних лексиконів та електронних текстових корпусів, автоматична обробка природної мови, автоматичний синтез та розпізнавання мовлення, машинний переклад, створення інтелектуальних роботів, здатних сприймати інформацію природною мовою. Для студентів та аспірантів гуманітарного профілю, науково-педагогічних працівників вищих навчальних закладів України

    Acta Cybernetica : Volume 19. Number 4.

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    CLiFF Notes: Research in the Language, Information and Computation Laboratory of the University of Pennsylvania

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    One concern of the Computer Graphics Research Lab is in simulating human task behavior and understanding why the visualization of the appearance, capabilities and performance of humans is so challenging. Our research has produced a system, called Jack, for the definition, manipulation, animation and human factors analysis of simulated human figures. Jack permits the envisionment of human motion by interactive specification and simultaneous execution of multiple constraints, and is sensitive to such issues as body shape and size, linkage, and plausible motions. Enhanced control is provided by natural behaviors such as looking, reaching, balancing, lifting, stepping, walking, grasping, and so on. Although intended for highly interactive applications, Jack is a foundation for other research. The very ubiquitousness of other people in our lives poses a tantalizing challenge to the computational modeler: people are at once the most common object around us, and yet the most structurally complex. Their everyday movements are amazingly fluid, yet demanding to reproduce, with actions driven not just mechanically by muscles and bones but also cognitively by beliefs and intentions. Our motor systems manage to learn how to make us move without leaving us the burden or pleasure of knowing how we did it. Likewise we learn how to describe the actions and behaviors of others without consciously struggling with the processes of perception, recognition, and language. Present technology lets us approach human appearance and motion through computer graphics modeling and three dimensional animation, but there is considerable distance to go before purely synthesized figures trick our senses. We seek to build computational models of human like figures which manifest animacy and convincing behavior. Towards this end, we: Create an interactive computer graphics human model; Endow it with reasonable biomechanical properties; Provide it with human like behaviors; Use this simulated figure as an agent to effect changes in its world; Describe and guide its tasks through natural language instructions. There are presently no perfect solutions to any of these problems; ultimately, however, we should be able to give our surrogate human directions that, in conjunction with suitable symbolic reasoning processes, make it appear to behave in a natural, appropriate, and intelligent fashion. Compromises will be essential, due to limits in computation, throughput of display hardware, and demands of real-time interaction, but our algorithms aim to balance the physical device constraints with carefully crafted models, general solutions, and thoughtful organization. The Jack software is built on Silicon Graphics Iris 4D workstations because those systems have 3-D graphics features that greatly aid the process of interacting with highly articulated figures such as the human body. Of course, graphics capabilities themselves do not make a usable system. Our research has therefore focused on software to make the manipulation of a simulated human figure easy for a rather specific user population: human factors design engineers or ergonomics analysts involved in visualizing and assessing human motor performance, fit, reach, view, and other physical tasks in a workplace environment. The software also happens to be quite usable by others, including graduate students and animators. The point, however, is that program design has tried to take into account a wide variety of physical problem oriented tasks, rather than just offer a computer graphics and animation tool for the already computer sophisticated or skilled animator. As an alternative to interactive specification, a simulation system allows a convenient temporal and spatial parallel programming language for behaviors. The Graphics Lab is working with the Natural Language Group to explore the possibility of using natural language instructions, such as those found in assembly or maintenance manuals, to drive the behavior of our animated human agents. (See the CLiFF note entry for the AnimNL group for details.) Even though Jack is under continual development, it has nonetheless already proved to be a substantial computational tool in analyzing human abilities in physical workplaces. It is being applied to actual problems involving space vehicle inhabitants, helicopter pilots, maintenance technicians, foot soldiers, and tractor drivers. This broad range of applications is precisely the target we intended to reach. The general capabilities embedded in Jack attempt to mirror certain aspects of human performance, rather than the specific requirements of the corresponding workplace. We view the Jack system as the basis of a virtual animated agent that can carry out tasks and instructions in a simulated 3D environment. While we have not yet fooled anyone into believing that the Jack figure is real , its behaviors are becoming more reasonable and its repertoire of actions more extensive. When interactive control becomes more labor intensive than natural language instructional control, we will have reached a significant milestone toward an intelligent agent

    On looking into words (and beyond): Structures, Relations, Analyses

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    On Looking into Words is a wide-ranging volume spanning current research into word structure and morphology, with a focus on historical linguistics and linguistic theory. The papers are offered as a tribute to Stephen R. Anderson, the Dorothy R. Diebold Professor of Linguistics at Yale, who is retiring at the end of the 2016-2017 academic year. The contributors are friends, colleagues, and former students of Professor Anderson, all important contributors to linguistics in their own right. As is typical for such volumes, the contributions span a variety of topics relating to the interests of the honorand. In this case, the central contributions that Anderson has made to so many areas of linguistics and cognitive science, drawing on synchronic and diachronic phenomena in diverse linguistic systems, are represented through the papers in the volume. The 26 papers that constitute this volume are unified by their discussion of the interplay between synchrony and diachrony, theory and empirical results, and the role of diachronic evidence in understanding the nature of language. Central concerns of the volume include morphological gaps, learnability, increases and declines in productivity, and the interaction of different components of the grammar. The papers deal with a range of linked synchronic and diachronic topics in phonology, morphology, and syntax (in particular, cliticization), and their implications for linguistic theory
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