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Proceedings of QG2010: The Third Workshop on Question Generation
These are the peer-reviewed proceedings of "QG2010, The Third Workshop on Question Generation". The workshop included a special track for "QGSTEC2010: The First Question Generation Shared Task and Evaluation Challenge".
QG2010 was held as part of The Tenth International Conference on Intelligent Tutoring Systems (ITS2010)
An investigation of the electrolytic plasma oxidation process for corrosion protection of pure magnesium and magnesium alloy AM50.
In this study, silicate and phosphate EPO coatings were produced on pure magnesium using an AC power source. It was found that the silicate coatings possess good wear resistance, while the phosphate coatings provide better corrosion protection. A Design of Experiment (DOE) technique, the Taguchi method, was used to systematically investigate the effect of the EPO process parameters on the corrosion protection properties of a coated magnesium alloy AM50 using a DC power. The experimental design consisted of four factors (treatment time, current density, and KOH and NaAlO2 concentrations), with three levels of each factor. Potentiodynamic polarization measurements were conducted to determine the corrosion resistance of the coated samples. The optimized processing parameters are 12 minutes, 12 mA/cm2 current density, 0.9 g/l KOH, 15.0 g/l NaAlO2. The results of the percentage contribution of each factor determined by the analysis of variance (ANOVA) imply that the KOH concentration is the most significant factor affecting the corrosion resistance of the coatings, while treatment time is a major factor affecting the thickness of the coatings. (Abstract shortened by UMI.)Dept. of Electrical and Computer Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2005 .M323. Source: Masters Abstracts International, Volume: 44-03, page: 1479. Thesis (M.A.Sc.)--University of Windsor (Canada), 2005
An investigation of grammar design in natural-language speech-recognition.
With the growing interest and demand for human-machine interaction, much work concerning speech-recognition has been carried out over the past three decades. Although a variety of approaches have been proposed to address speech-recognition issues, such as stochastic (statistical) techniques, grammar-based techniques, techniques integrated with linguistic features, and other approaches, recognition accuracy and robustness remain among the major problems that need to be addressed. At the state of the art, most commercial speech products are constructed using grammar-based speech-recognition technology. In this thesis, we investigate a number of features involved in grammar design in natural-language speech-recognition technology. We hypothesize that: with the same domain, a semantic grammar, which directly encodes some semantic constraints into the recognition grammar, achieves better accuracy, but less robustness; a syntactic grammar defines a language with a larger size, thereby it has better robustness, but less accuracy; a word-sequence grammar, which includes neither semantics nor syntax, defines the largest language, therefore, is the most robust, but has very poor recognition accuracy. In this Master\u27s thesis, we claim that proper grammar design can achieve the appropriate compromise between recognition accuracy and robustness. The thesis has been proven by experiments using the IBM Voice-Server SDK, which consists of a VoiceXML browser, IBM ViaVoice Speech Recognition and Text-To-Speech (TTS) engines, sample applications, and other tools for developing and testing VoiceXML applications. The experimental grammars are written in the Java Speech Grammar Format (JSGF), and the testing applications are written in VoiceXML. The tentative experimental results suggest that grammar design is a good area for further study. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2003 .S555. Source: Masters Abstracts International, Volume: 43-01, page: 0244. Adviser: Richard A. Frost. Thesis (M.Sc.)--University of Windsor (Canada), 2004
Survey of the State of the Art in Natural Language Generation: Core tasks, applications and evaluation
This paper surveys the current state of the art in Natural Language
Generation (NLG), defined as the task of generating text or speech from
non-linguistic input. A survey of NLG is timely in view of the changes that the
field has undergone over the past decade or so, especially in relation to new
(usually data-driven) methods, as well as new applications of NLG technology.
This survey therefore aims to (a) give an up-to-date synthesis of research on
the core tasks in NLG and the architectures adopted in which such tasks are
organised; (b) highlight a number of relatively recent research topics that
have arisen partly as a result of growing synergies between NLG and other areas
of artificial intelligence; (c) draw attention to the challenges in NLG
evaluation, relating them to similar challenges faced in other areas of Natural
Language Processing, with an emphasis on different evaluation methods and the
relationships between them.Comment: Published in Journal of AI Research (JAIR), volume 61, pp 75-170. 118
pages, 8 figures, 1 tabl
Probabilistic grammar induction from sentences and structured meanings
The meanings of natural language sentences may be represented as compositional
logical-forms. Each word or lexicalised multiword-element has an associated logicalform
representing its meaning. Full sentential logical-forms are then composed from
these word logical-forms via a syntactic parse of the sentence.
This thesis develops two computational systems that learn both the word-meanings
and parsing model required to map sentences onto logical-forms from an example corpus
of (sentence, logical-form) pairs. One of these systems is designed to provide a
general purpose method of inducing semantic parsers for multiple languages and logical
meaning representations. Semantic parsers map sentences onto logical representations
of their meanings and may form an important part of any computational task that
needs to interpret the meanings of sentences. The other system is designed to model
the way in which a child learns the semantics and syntax of their first language. Here,
logical-forms are used to represent the potentially ambiguous context in which childdirected
utterances are spoken and a psycholinguistically plausible training algorithm
learns a probabilistic grammar that describes the target language. This computational
modelling task is important as it can provide evidence for or against competing theories
of how children learn their first language.
Both of the systems presented here are based upon two working hypotheses. First,
that the correct parse of any sentence in any language is contained in a set of possible
parses defined in terms of the sentence itself, the sentence’s logical-form and a small
set of combinatory rule schemata. The second working hypothesis is that, given a
corpus of (sentence, logical-form) pairs that each support a large number of possible
parses according to the schemata mentioned above, it is possible to learn a probabilistic
parsing model that accurately describes the target language.
The algorithm for semantic parser induction learns Combinatory Categorial Grammar
(CCG) lexicons and discriminative probabilistic parsing models from corpora of
(sentence, logical-form) pairs. This system is shown to achieve at or near state of the art
performance across multiple languages, logical meaning representations and domains.
As the approach is not tied to any single natural or logical language, this system represents
an important step towards widely applicable black-box methods for semantic parser induction. This thesis also develops an efficient representation of the CCG lexicon
that separately stores language specific syntactic regularities and domain specific
semantic knowledge. This factorised lexical representation improves the performance
of CCG based semantic parsers in sparse domains and also provides a potential basis
for lexical expansion and domain adaptation for semantic parsers.
The algorithm for modelling child language acquisition learns a generative probabilistic
model of CCG parses from sentences paired with a context set of potential
logical-forms containing one correct entry and a number of distractors. The online
learning algorithm used is intended to be psycholinguistically plausible and to assume
as little information specific to the task of language learning as is possible. It is shown
that this algorithm learns an accurate parsing model despite making very few initial
assumptions. It is also shown that the manner in which both word-meanings and syntactic
rules are learnt is in accordance with observations of both of these learning tasks
in children, supporting a theory of language acquisition that builds upon the two working
hypotheses stated above
Toward Widely-Available and Usable Multimodal Conversational Interfaces
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.Cataloged from PDF version of thesis.Includes bibliographical references (p. 159-166).Multimodal conversational interfaces, which allow humans to interact with a computer using a combination of spoken natural language and a graphical interface, offer the potential to transform the manner by which humans communicate with computers. While researchers have developed myriad such interfaces, none have made the transition out of the laboratory and into the hands of a significant number of users. This thesis makes progress toward overcoming two intertwined barriers preventing more widespread adoption: availability and usability. Toward addressing the problem of availability, this thesis introduces a new platform for building multimodal interfaces that makes it easy to deploy them to users via the World Wide Web. One consequence of this work is City Browser, the first multimodal conversational interface made publicly available to anyone with a web browser and a microphone. City Browser serves as a proof-of-concept that significant amounts of usage data can be collected in this way, allowing a glimpse of how users interact with such interfaces outside of a laboratory environment. City Browser, in turn, has served as the primary platform for deploying and evaluating three new strategies aimed at improving usability. The most pressing usability challenge for conversational interfaces is their limited ability to accurately transcribe and understand spoken natural language. The three strategies developed in this thesis - context-sensitive language modeling, response confidence scoring, and user behavior shaping - each attack the problem from a different angle, but they are linked in that each critically integrates information from the conversational context.by Alexander Gruenstein.Ph.D
Artificial general intelligence: Proceedings of the Second Conference on Artificial General Intelligence, AGI 2009, Arlington, Virginia, USA, March 6-9, 2009
Artificial General Intelligence (AGI) research focuses on the original and ultimate goal of AI – to create broad human-like and transhuman intelligence, by exploring all available paths, including theoretical and experimental computer science, cognitive science, neuroscience, and innovative interdisciplinary methodologies. Due to the difficulty of this task, for the last few decades the majority of AI researchers have focused on what has been called narrow AI – the production of AI systems displaying intelligence regarding specific, highly constrained tasks. In
recent years, however, more and more researchers have recognized the necessity – and feasibility – of returning to the original goals of the field. Increasingly, there is a call for a transition back to confronting the more difficult issues of human level intelligence and more broadly artificial general intelligence
Hybrid discourse modeling and summarization for a speech-to-speech translation system
The thesis discusses two parts of the speech-to-speech translation system VerbMobil: the dialogue model and one of its applications, multilingual summary generation. In connection with the dialogue model, two topics are of special interest: (a) the use of a default unification operation called overlay as the fundamental operation for dialogue management; and (b) an intentional model that is able to describe intentions in dialogue on five levels in a language-independent way. Besides the actual generation algorithm developed, we present a comprehensive evaluation of the summarization functionality. In addition to precision and recall, a new characterization - confabulation - is defined that provides a more precise understanding of the performance of complex natural language processing systems.Die vorliegende Arbeit behandelt hauptsächlich zwei Themen, die für das VerbMobil-System, ein Übersetzungssystem gesprochener Spontansprache, entwickelt wurden: das Dialogmodell und als Applikation die multilinguale Generierung von Ergebnissprotokollen. Für die Dialogmodellierung sind zwei Themen von besonderem Interesse. Das erste behandelt eine in der vorliegenden Arbeit formalisierte Default-Unifikations-Operation namens Overlay, die als fundamentale Operation für Diskursverarbeitung dient. Das zweite besteht aus einem intentionalen Modell, das Intentionen eines Dialogs auf fünf Ebenen in einer sprachunabhängigen Repräsentation darstellt. Neben dem für die Protokollgenerierung entwickelten Generierungsalgorithmus wird eine umfassende Evaluation zur Protokollgenerierungsfunktionalität vorgestellt. Zusätzlich zu "precision" und "recall" wird ein neues Maß - Konfabulation (Engl.: "confabulation") - vorgestellt, das eine präzisere Charakterisierung der Qualität eines komplexen Sprachverarbeitungssystems ermöglicht