52 research outputs found
Korean Grammar Using TAGs
This paper addresses various issues related to representing the Korean language using Tree Adjoining Grammars. Topics covered include Korean grammar using TAGs, Machine Translation between Korean and English using Synchronous Tree Adjoining Grammars (STAGs), handling scrambling using Multi Component TAGs (MC-TAGs), and recovering empty arguments. The data for the parsing is from US military communication messages
CLiFF Notes: Research In Natural Language Processing at the University of Pennsylvania
CLIFF is the Computational Linguists\u27 Feedback Forum. We are a group of students and faculty who gather once a week to hear a presentation and discuss work currently in progress. The \u27feedback\u27 in the group\u27s name is important: we are interested in sharing ideas, in discussing ongoing research, and in bringing together work done by the students and faculty in Computer Science and other departments.
However, there are only so many presentations which we can have in a year. We felt that it would be beneficial to have a report which would have, in one place, short descriptions of the work in Natural Language Processing at the University of Pennsylvania. This report then, is a collection of abstracts from both faculty and graduate students, in Computer Science, Psychology and Linguistics. We want to stress the close ties between these groups, as one of the things that we pride ourselves on here at Penn is the communication among different departments and the inter-departmental work.
Rather than try to summarize the varied work currently underway at Penn, we suggest reading the abstracts to see how the students and faculty themselves describe their work. The report illustrates the diversity of interests among the researchers here, as well as explaining the areas of common interest. In addition, since it was our intent to put together a document that would be useful both inside and outside of the university, we hope that this report will explain to everyone some of what we are about
CLiFF Notes: Research In Natural Language Processing at the University of Pennsylvania
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
The Circle of Meaning: From Translation to Paraphrasing and Back
The preservation of meaning between inputs and outputs is perhaps
the most ambitious and, often, the most elusive goal of systems
that attempt to process natural language. Nowhere is this goal of
more obvious importance than for the tasks of machine translation
and paraphrase generation. Preserving meaning between the input and
the output is paramount for both, the monolingual vs bilingual distinction
notwithstanding. In this thesis, I present a novel, symbiotic relationship
between these two tasks that I term the "circle of meaning''.
Today's statistical machine translation (SMT) systems require high
quality human translations for parameter tuning, in addition to
large bi-texts for learning the translation units. This parameter
tuning usually involves generating translations at different points
in the parameter space and obtaining feedback against human-authored
reference translations as to how good the translations. This feedback
then dictates what point in the parameter space should be explored
next. To measure this feedback, it is generally considered wise to have
multiple (usually 4) reference translations to avoid unfair penalization of translation
hypotheses which could easily happen given the large number of ways in which
a sentence can be translated from one language to another. However, this reliance on multiple reference translations
creates a problem since they are labor intensive and expensive to obtain.
Therefore, most current MT datasets only contain a single reference.
This leads to the problem of reference sparsity---the primary open problem
that I address in this dissertation---one that has a serious effect on the
SMT parameter tuning process.
Bannard and Callison-Burch (2005) were the first to provide a practical
connection between phrase-based statistical machine translation and paraphrase
generation. However, their technique is restricted to generating phrasal
paraphrases. I build upon their approach and augment a phrasal paraphrase
extractor into a sentential paraphraser with extremely broad coverage.
The novelty in this augmentation lies in the further strengthening of
the connection between statistical machine translation and paraphrase
generation; whereas Bannard and Callison-Burch only relied on SMT machinery
to extract phrasal paraphrase rules and stopped there, I take it a few
steps further and build a full English-to-English SMT system. This system
can, as expected, ``translate'' any English input sentence into a new English
sentence with the same degree of meaning preservation that exists in a bilingual
SMT system. In fact, being a state-of-the-art SMT system, it is able to generate
n-best "translations" for any given input sentence. This sentential
paraphraser, built almost entirely from existing SMT machinery, represents
the first 180 degrees of the circle of meaning.
To complete the circle, I describe a novel connection in the other direction.
I claim that the sentential paraphraser, once built in this fashion, can
provide a solution to the reference sparsity problem and, hence, be used
to improve the performance a bilingual SMT system. I discuss two different
instantiations of the sentential paraphraser and show several results that
provide empirical validation for this connection
Dependency reordering features for Japanese-English phrase-based translation
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.Includes bibliographical references (p. 101-106).Translating Japanese into English is very challenging because of the vast difference in word order between the two languages. For example, the main verb is always at the very end of a Japanese sentence, whereas it comes near the beginning of an English sentence. In this thesis, we develop a Japanese-to-English translation system capable of performing the long-distance reordering necessary to fluently translate Japanese into English. Our system uses novel feature functions, based on a dependency parse of the input Japanese sentence, which identify candidate translations that put dependency relationships into correct English order. For example, one feature identifies translations that put verbs before their objects. The weights for these feature functions are discriminatively trained, and so can be used for any language pair. In our Japanese-to-English system, they improve the BLEU score from 27.96 to 28.54, and we show clear improvements in subjective quality. We also experiment with a well-known technique of training the translation system on a Japanese training corpus that has been reordered into an English-like word order. Impressive results can be achieved by naively reordering each Japanese sentence into reverse order. Translating these reversed sentences with the dependency-parse-based feature functions gives further improvement. Finally, we evaluate our translation systems with human judgment, BLEU score, and METEOR score. We compare these metrics on corpus and sentence level and examine how well they capture improvements in translation word order.by Jason Edward Katz-Brown.M.Eng
A Computational Model of Syntactic Processing: Ambiguity Resolution from Interpretation
Syntactic ambiguity abounds in natural language, yet humans have no
difficulty coping with it. In fact, the process of ambiguity resolution is
almost always unconscious. But it is not infallible, however, as example 1
demonstrates.
1. The horse raced past the barn fell.
This sentence is perfectly grammatical, as is evident when it appears in the
following context:
2. Two horses were being shown off to a prospective buyer. One was raced past
a meadow. and the other was raced past a barn. ...
Grammatical yet unprocessable sentences such as 1 are called `garden-path
sentences.' Their existence provides an opportunity to investigate the human
sentence processing mechanism by studying how and when it fails. The aim of
this thesis is to construct a computational model of language understanding
which can predict processing difficulty. The data to be modeled are known
examples of garden path and non-garden path sentences, and other results from
psycholinguistics.
It is widely believed that there are two distinct loci of computation in
sentence processing: syntactic parsing and semantic interpretation. One
longstanding controversy is which of these two modules bears responsibility for
the immediate resolution of ambiguity. My claim is that it is the latter, and
that the syntactic processing module is a very simple device which blindly and
faithfully constructs all possible analyses for the sentence up to the current
point of processing. The interpretive module serves as a filter, occasionally
discarding certain of these analyses which it deems less appropriate for the
ongoing discourse than their competitors.
This document is divided into three parts. The first is introductory, and
reviews a selection of proposals from the sentence processing literature. The
second part explores a body of data which has been adduced in support of a
theory of structural preferences --- one that is inconsistent with the present
claim. I show how the current proposal can be specified to account for the
available data, and moreover to predict where structural preference theories
will go wrong. The third part is a theoretical investigation of how well the
proposed architecture can be realized using current conceptions of linguistic
competence. In it, I present a parsing algorithm and a meaning-based ambiguity
resolution method.Comment: 128 pages, LaTeX source compressed and uuencoded, figures separate
macros: rotate.sty, lingmacros.sty, psfig.tex. Dissertation, Computer and
Information Science Dept., October 199
Recommended from our members
The Roles of Language Models and Hierarchical Models in Neural Sequence-to-Sequence Prediction
With the advent of deep learning, research in many areas of machine learning is converging towards the same set of methods and models. For example, long short-term memory networks are not only popular for various tasks in natural language processing (NLP) such as speech recognition, machine translation, handwriting recognition, syntactic parsing, etc., but they are also applicable to seemingly unrelated fields such as robot control, time series prediction, and bioinformatics. Recent advances in contextual word embeddings like BERT boast with achieving state-of-the-art results on 11 NLP tasks with the same model. Before deep learning, a speech recognizer and a syntactic parser used to have little in common as systems were much more tailored towards the task at hand.
At the core of this development is the tendency to view each task as yet another data mapping problem, neglecting the particular characteristics and (soft) requirements tasks often have in practice. This often goes along with a sharp break of deep learning methods with previous research in the specific area. This work can be understood as an antithesis to this paradigm. We show how traditional symbolic statistical machine translation models can still improve neural machine translation (NMT) while reducing the risk for common pathologies of NMT such as hallucinations and neologisms. Other external symbolic models such as spell checkers and morphology databases help neural grammatical error correction. We also focus on language models that often do not play a role in vanilla end-to-end approaches and apply them in different ways to word reordering, grammatical error correction, low-resource NMT, and document-level NMT. Finally, we demonstrate the benefit of hierarchical models in sequence-to-sequence prediction. Hand-engineered covering grammars are effective in preventing catastrophic errors in neural text normalization systems. Our operation sequence model for interpretable NMT represents translation as a series of actions that modify the translation state, and can also be seen as derivation in a formal grammar.EPSRC grant EP/L027623/1
EPSRC Tier-2 capital grant EP/P020259/
Grammatical theory: From transformational grammar to constraint-based approaches. Second revised and extended edition.
This book is superseded by the third edition, available at http://langsci-press.org/catalog/book/255.
This book introduces formal grammar theories that play a role in current linguistic theorizing (Phrase Structure Grammar, Transformational Grammar/Government & Binding, Generalized Phrase Structure Grammar, Lexical Functional Grammar, Categorial Grammar, Head-Driven Phrase Structure Grammar, Construction Grammar, Tree Adjoining Grammar). The key assumptions are explained and it is shown how the respective theory treats arguments and adjuncts, the active/passive alternation, local reorderings, verb placement, and fronting of constituents over long distances. The analyses are explained with German as the object language.
The second part of the book compares these approaches with respect to their predictions regarding language acquisition and psycholinguistic plausibility. The nativism hypothesis, which assumes that humans posses genetically determined innate language-specific knowledge, is critically examined and alternative models of language acquisition are discussed. The second part then addresses controversial issues of current theory building such as the question of flat or binary branching structures being more appropriate, the question whether constructions should be treated on the phrasal or the lexical level, and the question whether abstract, non-visible entities should play a role in syntactic analyses. It is shown that the analyses suggested in the respective frameworks are often translatable into each other. The book closes with a chapter showing how properties common to all languages or to certain classes of languages can be captured.
The book is a translation of the German book Grammatiktheorie, which was published by Stauffenburg in 2010. The following quotes are taken from reviews:
With this critical yet fair reflection on various grammatical theories, Müller fills what was a major gap in the literature. Karen Lehmann, Zeitschrift für Rezensionen zur germanistischen Sprachwissenschaft, 2012
Stefan Müller’s recent introductory textbook, Grammatiktheorie, is an astonishingly comprehensive and insightful survey for beginning students of the present state of syntactic theory. Wolfgang Sternefeld und Frank Richter, Zeitschrift für Sprachwissenschaft, 2012
This is the kind of work that has been sought after for a while [...] The impartial and objective discussion offered by the author is particularly refreshing. Werner Abraham, Germanistik, 2012
This book is a new edition of http://langsci-press.org/catalog/book/25
Superseded: Grammatical theory: From transformational grammar to constraint-based approaches. Second revised and extended edition.
This book is superseded by the third edition, available at http://langsci-press.org/catalog/book/255.
This book introduces formal grammar theories that play a role in current linguistic theorizing (Phrase Structure Grammar, Transformational Grammar/Government & Binding, Generalized Phrase Structure Grammar, Lexical Functional Grammar, Categorial Grammar, Head-Driven Phrase Structure Grammar, Construction Grammar, Tree Adjoining Grammar). The key assumptions are explained and it is shown how the respective theory treats arguments and adjuncts, the active/passive alternation, local reorderings, verb placement, and fronting of constituents over long distances. The analyses are explained with German as the object language.
The second part of the book compares these approaches with respect to their predictions regarding language acquisition and psycholinguistic plausibility. The nativism hypothesis, which assumes that humans posses genetically determined innate language-specific knowledge, is critically examined and alternative models of language acquisition are discussed. The second part then addresses controversial issues of current theory building such as the question of flat or binary branching structures being more appropriate, the question whether constructions should be treated on the phrasal or the lexical level, and the question whether abstract, non-visible entities should play a role in syntactic analyses. It is shown that the analyses suggested in the respective frameworks are often translatable into each other. The book closes with a chapter showing how properties common to all languages or to certain classes of languages can be captured.
The book is a translation of the German book Grammatiktheorie, which was published by Stauffenburg in 2010. The following quotes are taken from reviews:
With this critical yet fair reflection on various grammatical theories, Müller fills what was a major gap in the literature. Karen Lehmann, Zeitschrift für Rezensionen zur germanistischen Sprachwissenschaft, 2012
Stefan Müller’s recent introductory textbook, Grammatiktheorie, is an astonishingly comprehensive and insightful survey for beginning students of the present state of syntactic theory. Wolfgang Sternefeld und Frank Richter, Zeitschrift für Sprachwissenschaft, 2012
This is the kind of work that has been sought after for a while [...] The impartial and objective discussion offered by the author is particularly refreshing. Werner Abraham, Germanistik, 2012
This book is a new edition of http://langsci-press.org/catalog/book/25
Superseded: Grammatical theory: From transformational grammar to constraint-based approaches. Second revised and extended edition.
This book is superseded by the third edition, available at http://langsci-press.org/catalog/book/255.
This book introduces formal grammar theories that play a role in current linguistic theorizing (Phrase Structure Grammar, Transformational Grammar/Government & Binding, Generalized Phrase Structure Grammar, Lexical Functional Grammar, Categorial Grammar, Head-Driven Phrase Structure Grammar, Construction Grammar, Tree Adjoining Grammar). The key assumptions are explained and it is shown how the respective theory treats arguments and adjuncts, the active/passive alternation, local reorderings, verb placement, and fronting of constituents over long distances. The analyses are explained with German as the object language.
The second part of the book compares these approaches with respect to their predictions regarding language acquisition and psycholinguistic plausibility. The nativism hypothesis, which assumes that humans posses genetically determined innate language-specific knowledge, is critically examined and alternative models of language acquisition are discussed. The second part then addresses controversial issues of current theory building such as the question of flat or binary branching structures being more appropriate, the question whether constructions should be treated on the phrasal or the lexical level, and the question whether abstract, non-visible entities should play a role in syntactic analyses. It is shown that the analyses suggested in the respective frameworks are often translatable into each other. The book closes with a chapter showing how properties common to all languages or to certain classes of languages can be captured.
The book is a translation of the German book Grammatiktheorie, which was published by Stauffenburg in 2010. The following quotes are taken from reviews:
With this critical yet fair reflection on various grammatical theories, Müller fills what was a major gap in the literature. Karen Lehmann, Zeitschrift für Rezensionen zur germanistischen Sprachwissenschaft, 2012
Stefan Müller’s recent introductory textbook, Grammatiktheorie, is an astonishingly comprehensive and insightful survey for beginning students of the present state of syntactic theory. Wolfgang Sternefeld und Frank Richter, Zeitschrift für Sprachwissenschaft, 2012
This is the kind of work that has been sought after for a while [...] The impartial and objective discussion offered by the author is particularly refreshing. Werner Abraham, Germanistik, 2012
This book is a new edition of http://langsci-press.org/catalog/book/25
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