Input: Novel Reordering Approaches In Phrase-Based Statistical Machine Translation This paper presents novel approaches to reordering in phrase-based statistical machine translation. We perform consistent reordering of source sentences in training and estimate a statistical translation model. Using this model, we follow a phrase-based monotonic machine translation approach, for which we develop an efficient and flexible reordering framework that allows to easily introduce different reordering constraints. In translation, we apply source sentence reordering on word level and use a reordering automaton as input. We show how to compute reordering automata on-demand using IBM or ITG constraints, and also introduce two new types ofreordering constraints. We further add weights to the reordering automata. We present detailed experimental results and show that reordering significantly improves translation quality.

paper

approaches

phrase-based

statistical machine translation

perform

source sentences

training

statistical translation model

model

phrase-based

machine translation

approach

develop

framework

constraints

translation

apply

source sentence

word

level

input

compute

constraints

types

constraints

weights

experimental

results

improves

translation quality

paper

approaches


Input: Handling Unlike Coordinated Phrases In TAG By Mixing Syntactic Category And Grammatical Function Coordination of phrases of different syntactic categories has posed a problem for generative systems based only on syntactic categories. Although some prefer to treat them as exceptional cases that should require some extra mechanism (as for elliptical constructions), or to allow for unrestricted cross-category coordination, they can be naturally derived in a grammatic functional generative approach. In this paper we explore the ideia on how mixing syntactic categories and grammatical functions in the label set of a Tree Adjoining Grammar allows us to develop grammars that elegantly handle both the cases of same-and cross-category coordination in an uniform way.

Coordination

phrases

syntactic categories

problem

systems

based

syntactic categories

cases

require

mechanism

constructions

cross-category

coordination

approach

paper

syntactic categories

grammatical functions

Tree Adjoining Grammar

develop

cases

cross-category

coordination

syntactic categories

systems

paper

Tree Adjoining Grammar


Input: From Concrete To Virtual Annotation Mark-Up Language: The Case Of COMMOn-REFs This work presents thedata model we adopted for annotating coreference. Ourdata model includes different levels of annotation, such as part-of-speech, syntax and discourse. We compare our encoding schemes to the abstract XML encoding being proposed as standard. We also present our tool for coreference resolution that handles ourdata model.

thedata

model

Ourdata

model

includes

levels

part-of-speech

syntax

discourse

schemes

abstract

proposed

standard

tool

coreference resolution

ourdata

model

schemes

standard

tool

coreference resolution


Input: Contextual Bitext-Derived Paraphrases In Automatic MT Evaluation In this paper we present a novel method for deriving paraphrases during automatic MT evaluation using only the source and reference texts, which are necessary for the evaluation, and word and phrase alignment software. Using target language paraphrases produced through word and phrase alignment a number of alternative reference sentences are constructed automatically for each candidate translation. The method produces lexical and low-level syntactic paraphrases that are relevant to the domain in hand, does not use external knowledge resources, and can be combined with a variety of automatic MT evaluation system.

paper

method

automatic

MT evaluation

source

reference

texts

evaluation

word

phrase

alignment

software

target language

word

phrase

alignment

number

alternative

reference

sentences

constructed

candidate

translation

method

lexical

low-level

syntactic

domain

hand

knowledge

resources

variety

automatic

MT evaluation

system

paper

method

texts

MT evaluation


Input: Backbone Extraction And Pruning For Speeding Up A Deep Parser For Dialogue Systems In this paper we discuss issues related to speeding up parsing with wide-coverage unification grammars. We demonstrate that state-of-the-art optimisation techniques based on backbone parsing before unification do not provide a general solution, because they depend on specific properties of the grammar formalism that do not hold for all unification based grammars. As an alternative, we describe an optimisation technique that combines ambiguity packing at the constituent structure level with pruning based on local features.

paper

issues

speeding

parsing

wide-coverage

unification

techniques

based

backbone

parsing

unification

provide

solution

properties

formalism

unification

based

alternative

technique

ambiguity

constituent structure

level

based

features

paper

parsing

parsing

techniques

properties

formalism


Input: Calibrating Features For Semantic Role Labeling This paper takes a critical look at the features used in the semantic role tagging literature and show that the information in the input, generally a syntactic parse tree, has yet to be fully exploited. We propose an additional set of features and our experiments show that these features lead to fairly significant improvements in the tasks we performed. We further show that different features are needed for different sub-tasks. Finally, we show that by using a Maximum Entropy classifier and fewer features, we achieved results comparable with the best previously reported results obtained with SVM models. We believe this is a clear indication that developing features that capture the right kind of information is crucial to advancing the state-of-the-art in semantic analysis.

paper

features

semantic role

tagging

literature

information

input

syntactic

parse tree

propose

features

experiments

features

improvements

tasks

performed

features

Maximum Entropy

classifier

features

results

reported

results

models

developing

features

kind

information

advancing

semantic analysis

paper

tagging

information

input

results

results


Input: The Entropy Rate Principle As A Predictor Of Processing Effort: An Evaluation Against Eye-Tracking Data This paper provides evidence for Genzel and Char-niak' s (2002) entropy rate principle, which predicts that the entropy of a sentence increases with its position in the text. We show that this principle holds for individual sentences (not just for averages), but we also find that the entropy rate effect is partly an artifact of sentence length, which also correlates with sentence position. Secondly, we evaluate a set of predictions that the entropy rate principle makes for human language processing; using a corpus of eye-tracking data, we show that entropy and processing effort are correlated, and that processing effort is constant throughout a text.

paper

provides

evidence

entropy

rate

principle

entropy

sentence

increases

text

principle

individual

sentences

entropy

rate

effect

sentence

length

sentence

evaluate

predictions

entropy

rate

principle

human language

processing

corpus

entropy

processing

effort

processing

effort

text

entropy

sentence


Input: MUC-7 Named Entity Task Definition (Version 3. 5) " The Named Entity task consists of three subtasks (entity names, temporal expressions, number expressions). The expressions to be annotated are " unique identifiers " of entities (organizations, persons, locations), times (dates, times), and quantities (monetary values, percentages). For many text processing systems, such identifiers are recognized primarily using local pattern-matching techniques. The TEI (Text Encoding Initiative) Guidelines for Electronic Text Encoding and Interchange cover such identifiers (plus abbreviations) together in section 6. 4 and explain that the identifiers comprise " textual features which it is often convenient to distinguish from their surrounding text. Names, dates and numbers are likely to be of particular importance to the scholar treating a text as source for a database; distinguishing such items from the surrounding text is however equally important to the scholar primarily interested in lexis. " The task is to identify all instances of the three types of expressions in each text in the test set and to subcategorize the expressions. The original texts contain some SGML tags already; the Named Entity task is to be performed within the text delimited by the SLUG, DATE, NWORDS, PREAMBLE, TEXT, and TRAILER tags. The system must produce a single, unambiguous output for any relevant string in the text; thus, this evaluation is not based on a view of a pipelined system architecture in which Named Entity recognition would be completely handled as a preprocess to sentence and discourse analysis. The task requires that the system recognize what a string represents, not just its superficial appearance. Sometimes, the right answer is superficially apparent, as in the case of most, if not all, NUMEX expressions, and can be obtained by local pattern-matching techniques. In other cases, the right answer is not superficially apparent, as when a single capitalized word could represent the name of a location, person, or organization, and the answer may have to be obtained using techniques that draw information from a larger context or from reference lists. The three subtasks correspond to three SGML tag elements: ENAMEX, TIMEX, and NUMEX. The subcategorization is captured by a SGML tag attribute called TYPE, which is defined to have a different set of possible values for each tag element. The markup is described in section 2, below. "

Named

Entity

task

entity

names

expressions

number

expressions

expressions

identifiers

entities

organizations

locations

times

dates

times

quantities

percentages

text processing

systems

identifiers

pattern-matching

techniques

Text

Initiative

Guidelines

Text

identifiers

abbreviations

section

identifiers

features

text

Names

dates

numbers

importance

text

source

database

items

text

task

instances

types

expressions

text

test set

expressions

texts

tags

Named

Entity

task

performed

text

DATE

TEXT

tags

system

output

string

text

evaluation

based

system architecture

Named

Entity

recognition

sentence

discourse analysis

task

requires

system

string

case

expressions

pattern-matching

techniques

cases

word

name

location

organization

techniques

information

context

reference

lists

tag

tag

called

TYPE

tag

markup

section

techniques

systems

features

identifiers

expressions

text

tags

texts

output

string

system architecture

evaluation

system

task

information

lists


Input: Semi-supervised Algorithm for Human-Computer Dialogue Mining This paper describes the analysis of weak local coherence utterances during human-computer conversation through the application of an emergentdata mining technique, data crystallization.

paper

analysis

coherence

utterances

human-computer

conversation

application

emergentdata

technique

data

analysis

utterances


Input: Implementation of the Arabic Numerals and their Syntax in GF The numeral system of Arabic is rich in its morphosyntactic variety yet suffers from the lack of a good computational resource that describes it in a reusable way. This implies that applications that require the use of rules of the Arabic numeral system have to either reimplement them each time, which implies wasted resources, or use simplified, imprecise rules that result in low quality applications. A solution has been devised with Grammatical Framework (GF) to use language constructs and grammars as libraries that can be written once and reused in various applications. In this paper, we describe our implementation of the Arabic numeral system, as an example of a bigger implementation of a grammar library for Arabic. We show that users can reuse our system by accessing a simple language-independent API rule.

system

variety

lack

computational

resource

applications

require

rules

system

time

resources

rules

result

quality

applications

solution

Framework

language

constructs

libraries

applications

paper

implementation

system

example

implementation

library

users

system

accessing

simple

language-independent

rule

rules

applications

resources

system

libraries

applications

paper

implementation


Input: Local Ambiguity Packing and Discontinuity in German We report on recent advances in HPSG parsing of German with local ambiguity packing (Oepen and Carroll, 2000), achieving a speed-up factor of 2 on a balanced test-suite. In contrast to earlier studies carried out for English using the same packing algorithm, we show that restricting semantic features only is insufficient for achieving acceptable runtime performance with a German HPSG grammar. In a series of experiments relating to the three different types of discontinuities in German (head movement, extraction, extraposition), we examine the effects of re-strictor choice, ultimately showing that extraction and head movement require partial restriction of the respective features encoding the dependency, whereas full restriction gives best results for extraposition.

report

advances

parsing

ambiguity

speed-up

factor

test-suite

contrast

studies

English

algorithm

semantic features

performance

series

experiments

types

extraction

effects

choice

extraction

require

partial

restriction

features

dependency

restriction

results

advances

parsing

studies

English

features

dependency

restriction

results


Input: Discontinuity Revisited: An Improved Conversion to Context-Free Representations This paper introduces a new, reversible method for converting syntactic structures with discontinuous constituents into traditional syntax trees. The method is applied to the Tiger Corpus of German and results for PCFG parsing requiring such context-free trees are provided. A labeled dependency evaluation shows that the new conversion method leads to better results by preserving local relationships and introducing fewer inconsistencies into the trainingdata.

paper

method

syntactic structures

constituents

syntax

trees

method

applied

Tiger

Corpus

results

parsing

requiring

context-free

trees

provided

dependency

evaluation

conversion

method

results

relationships

inconsistencies

trainingdata

trainingdata

paper

method

constituents

syntactic structures

method

Corpus

trees

parsing

method

results

inconsistencies

trainingdata


Input: IGT-XML: An XML Format for Interlinearized Glossed Text We propose a new XML format for representing interlinearized glossed text (IGT), particularly in the context of the documentation and description of endangered languages. The proposed representation, which we call IGT-XML, builds on previous models but provides a more loosely coupled and flexible representation of different annotation layers. Designed to accommodate both selective manual reannotation of individual layers and semi-automatic extension of annotation, IGT-XML is a first step toward partial automation of the production of IGT.

propose

format

text

context

documentation

description

languages

proposed

representation

call

models

provides

representation

layers

manual

individual

layers

semi-automatic

extension

first step

partial

automation

format

text


Input: Treebank Annotation Schemes and Parser Evaluation for German Recent studies focussed on the question whether less-configurational languages like German are harder to parse than English, or whether the lower parsing scores are an artefact of treebank encoding schemes anddata structures, as claimed by Kiibler et al. (2006). This claim is based on the assumption that PARSEVAL metrics fully reflect parse quality across treebank encoding schemes. In this paper we present new experiments to test this claim. We use the PARSEVAL metric, the Leaf-Ancestor metric as well as a dependency-based evaluation, and present novel approaches measuring the effect of controlled error insertion on treebank trees and parser output. We also provide extensive past-parsing cross-treebank conversion. The results of the experiments show that, contrary to Kubler et al. (2006), the question whether or not German is harder to parse than English remains undecided.

studies

question

languages

parse

English

parsing

schemes

anddata

structures

claimed

claim

based

assumption

metrics

parse

quality

schemes

paper

experiments

test

claim

metric

metric

dependency-based

evaluation

approaches

effect

error

insertion

trees

parser

output

provide

past-parsing

cross-treebank

conversion

results

experiments

question

parse

English

paper

experiments


Input: The Infinite PCFG Using Hierarchical Dirichlet Processes We present a nonparametric Bayesian model of tree structures based on the hierarchical Dirichlet process (HDP). Our HDP-PCFG model allows the complexity of the grammar to grow as more trainingdata is available. In addition to presenting a fully Bayesian model for the PCFG, we also develop an efficient variational inference procedure. On synthetic data, we recover the correct grammar without having to specify its complexity in advance. We also show that our techniques can be applied to full-scale parsing applications by demonstrating its effectiveness in learning state-split grammars.

model

tree structures

based

process

model

complexity

trainingdata

trainingdata

addition

model

develop

inference

procedure

complexity

advance

techniques

applied

full-scale

parsing

applications

effectiveness

model

tree structures

trainingdata

model

techniques

applications


Input: Web-Based Frequency Dictionaries For Medium Density Languages Frequency dictionaries play an important role both in psycholinguistic experiment design and in language technology. The paper describes a new, freely available, web-based frequency dictionary of Hungarian that is being used for both purposes, and the language-independent techniques used for creating it.

Frequency

dictionaries

role

experiment

design

language technology

paper

frequency

dictionary

purposes

language-independent

techniques

dictionaries

language technology

techniques

dictionary


Input: Automatic Identification Of English Verb Particle Constructions Using Linguistic Features This paper presents a method for identifying token instances of verb particle constructions (VPCs) automatically, based on the output of the RASP parser. The proposed method pools together instances of VPCs and verb-PPs from the parser output and uses the sentential context of each such instance to differentiate VPCs from verb-PPs. We show our technique to perform at an F-score of 97. 4% at identifying VPCs in Wall Street Journal and Brown Corpusdata taken from the Penn Tree-bank.

paper

method

instances

verb

particle

constructions

based

output

parser

proposed

method

instances

verb-

parser

output

context

instance

verb-

technique

perform

Wall Street Journal

Brown Corpusdata

Corpusdata

Tree-bank

paper

method

Corpusdata

Tree-bank


Input: Coreference Resolution Using Semantic Relatedness Information from Automatically Discovered Patterns Semantic relatedness is a very important factor for the coreference resolution task. To obtain this semantic information, corpus-based approaches commonly leverage patterns that can express a specific semantic relation. The patterns, however, are designed manually and thus are not necessarily the most effective ones in terms of accuracy and breadth. To deal with this problem, in this paper we propose an approach that can automatically find the effective patterns for coreference resolution. We explore how to automatically discover and evaluate patterns, and how to exploit the patterns to obtain the semantic relatedness information. The evaluation on ACEdata set shows that the pattern based semantic information is helpful for coreference resolution.

Semantic

relatedness

factor

coreference resolution

task

semantic information

corpus-based approaches

leverage

patterns

semantic relation

patterns

designed

terms

accuracy

deal

problem

paper

propose

approach

patterns

coreference resolution

evaluate

patterns

patterns

semantic

relatedness

information

evaluation

ACEdata

ACEdata

pattern

based

semantic information

coreference resolution

patterns

semantic relation

paper

approach

patterns

coreference resolution

semantic information

coreference resolution


Input: Words and Echoes: Assessing and Mitigating the Non-Randomness Problem in Word Frequency Distribution Modeling Frequency distribution models tuned to words and other linguistic events can predict the number of distinct types and their frequency distribution in samples of arbitrary sizes. We conduct, for the first time, a rigorous evaluation of these models based on cross-validation and separation of training and testdata. Our experiments reveal that the prediction accuracy of the models is marred by serious overfitting problems, due to violations of the random sampling assumption in corpusdata. We then propose a simple pre-processing method to alleviate such non-randomness problems. Further evaluation confirms the effectiveness of the method, which compares favourably to more complex correction techniques. different degrees in thedata (Baayen, 1992). Consider for example a very common prefix such as re-meta-. metametahow many typos are there on the Internet?)

Frequency

distribution

models

words

events

number

types

frequency

distribution

samples

sizes

time

evaluation

models

based

cross-validation

training

testdata

testdata

experiments

prediction

accuracy

models

marred

problems

due

sampling

assumption

corpusdata

corpusdata

propose

simple

pre-processing

method

problems

evaluation

effectiveness

method

complex

correction

techniques

degrees

thedata

example

common

prefix

sizes

samples

cross-validation

evaluation

models

accuracy


Input: Shallow Dependency Labeling We present a formalization of dependency labeling with Integer Linear Programming. We focus on the integration of subcatego-rization into the decision making process, where the various subcategorization frames of a verb compete with each other. A maximum entropy model provides the weights for ILP optimization.

formalization

dependency

Integer Linear Programming

focus

integration

decision

process

frames

verb

maximum entropy model

provides

weights

optimization

Integer Linear Programming

formalization


Input: EM Can Find Pretty Good HMM POS-Taggers (When Given a Good Start) We address the task of unsupervised POS tagging. We demonstrate that good results can be obtained using the robust EM-HMM learner when provided with good initial conditions, even with incomplete dictionaries. We present a family of algorithms to compute effective initial estimations p (t \ w).

task

POS tagging

results

robust

provided

dictionaries

algorithms

compute

estimations

algorithms

compute


Input: Adapting a WSJ-Trained Parser to Grammatically Noisy Text We present a robust parser which is trained on a treebank of ungrammatical sentences. The treebank is created automatically by modifying Penn treebank sentences so that they contain one or more syntactic errors. We evaluate an existing Penn-treebank-trained parser on the ungrammatical treebank to see how it reacts to noise in the form of grammatical errors. We re-train this parser on the training section of the ungrammatical treebank, leading to an significantly improved performance on the ungrammatical test sets. We show how a classifier can be used to prevent performance degradation on the original grammaticaldata.

robust

parser

trained

sentences

Penn treebank

sentences

syntactic

errors

evaluate

parser

noise

form

errors

re-train

parser

training

section

improved

performance

test sets

classifier

performance

degradation

grammaticaldata

errors

sentences

degradation

grammaticaldata


Input: Book Reviews: Incremental Conceptualization for Language Production by Markus Guhe " For the past ten years or more, most work in the field of Natural Language Generation (NLG) has shied away from considerations regarding the processes underlying human language production. Rather, the focus has been on systems that automatically produce language usually text from non-linguistic representations, with the main objective being generation of a text that faithfully captures the meaning of those non-linguistic representations (see, e. g., Reiter and Dale' s 2000 textbook on NLG). There is, however, also a different take on NLG " as not just competent performance by a computer but the development of a computational theory of the human capacity for language and processes that engage it " (McDonald 1987, page 642). Guhe' s research monograph, based on his 2003 Ph. D. thesis, is firmly situated in the latter tradition. One of his main goals is to work out a computational architecture for Levelt' s (1989) psycholinguistically motivated model of language production. According to Levelt' s model, speaking involves three main activities: conceptualizing (deciding what to say), formulating (deciding how to say it), and articulating (saying it). Guhe' s book focuses on the mental activity of conceptualizing. Conceptualizing is a recalcitrant object of study, partly because of the problem of the " initial spark "; the decision to say something appears to be the result of volitional conscious decisions, which largely elude scientific study. Guhe avoids this problem by investigating conceptualization in settings where the main intention is already fixed: a speaker witnesses several events unfold and is instructed to describe what happens "

field

Natural Language Generation

considerations

processes

human language

focus

systems

language

text

representations

main

objective

generation

text

representations

performance

computer

development

computational

theory

capacity

language

processes

page

research

based

thesis

main

goals

computational

architecture

model

language production

model

main

focuses

object

study

problem

decision

result

decisions

study

problem

main

events

model

language production


Input: First ideas of user-adapted views of lexicographicdata exemplified on OWID and elexiko This paper is a project report of the lexicographic Internet portal OWID, an Online Vocabulary Information System of German which is being built at the Institute of German Language in Mannheim (IDS). Overall, the contents of the portal and its technical approaches will be presented. The lexical database is structured in a granular way which allows to extend possible search options for lexicographers. Against the background of current research on using electronic dictionaries, the project OWID is also working on first ideas of user-adapted access and user-adapted views of the lexicographicdata. Due to the fact that the portal OWID comprises dictionaries which are available online it is possible to change the design and functions of the website easily (in comparison to printed dictionaries). Ideas of implementing user-adapted views of the lexicographicdata will be demonstrated by using an example taken from one of the dictionaries of the portal, namely elexiko.

paper

project

report

Vocabulary

Information System

Language

approaches

lexical database

structured

search

options

background

current

research

electronic dictionaries

project

user-adapted

access

user-adapted

lexicographicdata

Due

dictionaries

design

functions

comparison

dictionaries

implementing

user-adapted

lexicographicdata

example

dictionaries

example

dictionaries


Input: Probabilistic Model for Syntactic and Semantic Dependency Parsing This paper proposes a novel method to analyze syntactic dependencies and label semantic dependencies around both the verbal predicates and the nouns. In this method, a probabilistic model is designed to obtain a global optimal result. Moreover, a predicate identification model and a disambiguation model are proposed to label predicates and their senses. The experimental results obtained on the wsj and brown test sets show that our system obtains 77% of labeled macro F1 score for the whole task, 84. 47% of labeled attachment score for syntactic dependency task, and 69. 45% of labeled F1 score for semantic dependency task.

paper

proposes

method

syntactic

dependencies

semantic

dependencies

verbal

nouns

method

probabilistic model

designed

optimal

result

identification

model

disambiguation

model

proposed

experimental

results

test sets

system

task

attachment

syntactic

dependency

task

semantic

dependency

task

paper

method

probabilistic model

result


Input: Are Very Large N-Best Lists Useful for SMT? This paper describes an efficient method to extract large n-best lists from a word graph produced by a statistical machine translation system. The extraction is based on the k shortest paths algorithm which is efficient even for very large k. We show that, although we can generate large amounts of distinct translation hypotheses, these numerous candidates are not able to significantly improve overall system performance. We conclude that large n-best lists would benefit from better discriminating models.

paper

method

extract

lists

word

statistical machine translation system

extraction

based

paths

algorithm

generate

amounts

translation

hypotheses

candidates

improve

system

performance

lists

benefit

models

paper

method

algorithm

extraction


Input: A Word-Order Database For Testing Computational Models Of Language Acquisition An investment of effort over the last two years has begun to produce a wealth ofdata concerning computational psycholin-guistic models of syntax acquisition. Thedata is generated by running simulations on a recently completed database of word order patterns from over 3, 000 abstract languages. This article presents the design of the database which contains sentence patterns, grammars and derivations that can be used to test acquisition models from widely divergent paradigms. The domain is generated from grammars that are linguistically motivated by current syntactic theory and the sentence patterns have been validated as psychologically/developmen-tally plausible by checking their frequency of occurrence in corpora of child-directed speech. A small case-study simulation is also presented.

effort

ofdata

concerning

computational

models

syntax

acquisition

Thedata

generated

simulations

database

word

order

patterns

abstract

languages

design

database

sentence

patterns

derivations

test

acquisition

models

paradigms

domain

generated

current

syntactic

theory

sentence

patterns

checking

frequency

occurrence

corpora

speech

case-study

simulation

patterns

database

patterns

database

speech

corpora


Input: Deverbal Compound Noun Analysis Based On Lexical Conceptual Structure This paper proposes a principled approach for analysis of semantic relations between constituents in compound nouns based on lexical semantic structure. One of the difficulties of compound noun analysis is that the mechanisms governing the decision system of semantic relations and the representation method of semantic relations associated with lexical and contextual meaning are not obvious. The aim of our research is to clarify how lexical semantics contribute to the relations in compound nouns since such nouns are very productive and are supposed to be governed by systematic mechanisms. The results of applying our approach to the analysis of noun-deverbal compounds in Japanese and English show that lexical conceptual structure contributes to the re-strictional rules in compounds.

paper

proposes

approach

analysis

semantic relations

constituents

nouns

based

lexical

semantic structure

difficulties

noun

analysis

mechanisms

decision

system

semantic relations

representation

method

semantic relations

lexical

research

lexical semantics

relations

nouns

nouns

mechanisms

results

applying

approach

analysis

noun-deverbal

Japanese

English

lexical

conceptual structure

rules

paper

approach

analysis

semantic relations


Input: Computing Locally Coherent Discourses We present the first algorithm that computes optimal orderings of sentences into a locally coherent discourse. The algorithm runs very efficiently on a variety of coherence measures from the literature. We also show that the discourse ordering problem is NP-complete and cannot be approximated.

algorithm

computes

optimal

sentences

discourse

algorithm

variety

coherence

literature

discourse

ordering

problem

algorithm

sentences


Input: Multi-Engine Machine Translation With Voted Language Model The paper describes a particular approach to multi-engine machine translation (MEMT), where we make use of voted language models to selectively combine translation outputs from multiple off-the-shelf MT systems. Experiments are done using large corpora from three distinct domains. The study found that the use of voted language models leads to an improved performance of MEMT systems.

paper

approach

multi-engine

machine translation

language models

translation

outputs

MT systems

Experiments

corpora

domains

study

language models

improved

performance

systems

paper

approach

language models

machine translation

corpora

Experiments

language models

performance


Input: A Unified Framework For Automatic Evaluation Using N-Gram Co-Occurrence Statistics In this paper we propose a unified framework for automatic evaluation of NLP applications using N-gram co-occurrence statistics. The automatic evaluation metrics proposed to date for Machine Translation and Automatic Summarization are particular instances from the family of metrics we propose. We show that different members of the same family of metrics explain best the variations obtained with human evaluations, according to the application being evaluated (Machine Translation, Automatic Summarization, and Automatic Question Answering) and the evaluation guidelines used by humans for evaluating such applications.

paper

propose

framework

automatic evaluation

NLP applications

gram

co-occurrence

statistics

evaluation metrics

proposed

date

Machine Translation

Automatic Summarization

instances

metrics

propose

metrics

variations

evaluations

application

evaluated

Machine Translation

Automatic Summarization

Automatic

Question Answering

evaluation

guidelines

evaluating

applications

paper

framework

statistics

NLP applications

evaluation metrics

Machine Translation

variations

evaluations


Input: MT Evaluation: Human-Like Vs. Human Acceptable We present a comparative study on Machine Translation Evaluation according to two different criteria: Human Likeness and Human Acceptability. We provide empirical evidence that there is a relationship between these two kinds of evaluation: Human Likeness implies Human Acceptability but the reverse is not true. From the point of view of automatic evaluation this implies that metrics based on Human Likeness are more reliable for system tuning. Our results also show that current evaluation metrics are not always able to distinguish between automatic and human translations. In order to improve the descriptive power of current metrics we propose the use of additional syntax-based metrics, and metric combinations inside the QARLA Framework.

study

Machine Translation Evaluation

criteria

provide

evidence

relationship

kinds

evaluation

point of view

automatic evaluation

metrics

based

system

results

current

evaluation metrics

automatic

translations

order

improve

current

metrics

propose

syntax-based

metrics

metric

combinations

Framework

metrics

Framework


Input: Examining The Content Load Of Part Of Speech Blocks For Information Retrieval We investigate the connection between part of speech (POS) distribution and content in language. We define POS blocks to be groups of parts of speech. We hypothesise that there exists a directly proportional relation between the frequency of POS blocks and their content salience. We also hypothesise that the class membership of the parts of speech within such blocks reflects the content load of the blocks, on the basis that open class parts of speech are more content-bearing than closed class parts of speech. We test these hypotheses in the context of Information Retrieval, by syntactically representing queries, and removing from them content-poor blocks, in line with the aforementioned hypotheses. For our first hypothesis, we induce POS distribution information from a corpus, and approximate the probability of occurrence of POS blocks as per two statistical estimators separately. For our second hypothesis, we use simple heuristics to estimate the content load within POS blocks. We use the Text REtrieval Conference (TREC) queries of 1999 and 2000 to retrieve documents from the WT2G and WT10G test collections, with five different retrieval strategies. Experimental outcomes confirm that our hypotheses hold in the context of Information Retrieval.

part of speech

distribution

content

language

parts of speech

relation

frequency

content

class

parts of speech

content

basis

class

parts of speech

content-bearing

class

parts of speech

test

hypotheses

context

Information Retrieval

queries

content-poor

hypotheses

hypothesis

distribution

information

corpus

probability

occurrence

statistical

hypothesis

simple

content

Text REtrieval Conference

queries

documents

test

collections

retrieval

strategies

Experimental

outcomes

hypotheses

context

Information Retrieval

information

corpus


Input: Integrated Morphological And Syntactic Disambiguation For Modern Hebrew Current parsing models are not immediately applicable for languages that exhibit strong interaction between morphology and syntax, e. g., Modern Hebrew (MH), Arabic and other Semitic languages. This work represents a first attempt at modeling morphological-syntactic interaction in a generative probabilistic framework to allow for MH parsing. We show that morphological information selected in tandem with syntactic categories is instrumental for parsing Semitic languages. We further show that redundant morphological information helps syntactic disambiguation.

Current

parsing

models

languages

interaction

morphology

syntax

languages

modeling

morphological-syntactic

interaction

framework

parsing

information

syntactic categories

parsing

languages

information

helps

syntactic

disambiguation

models

languages

framework

parsing

parsing

languages

information

disambiguation


Input: Lexical Parallelism In Text Structure Determination And Content Analysis In this paper the problem is discussed about the text structure determination and content analysis by lexical parallelism, or the repetition of lexical items. Intersentential relations are determined through the identical, partly identical or lexico-semantic repetition in Japanese scientific texts. Lexical parallelism ratio and lexical parallelism indicator distance are obtained on computer and by hand. And the application of the characteristics to automatic content analysis is dicsussed.

paper

problem

text structure

determination

content

analysis

lexical

repetition

lexical items

relations

lexico-semantic

repetition

Japanese

texts

Lexical

parallelism

ratio

lexical

parallelism

indicator

distance

computer

hand

application

characteristics

automatic

content

analysis

repetition

lexical items

repetition

texts


Input: Toward A Parsing Method For Free Word Order Languages " Free word order " is a traditional term that should not be taken literally. However, we shall retain the term for its conciseness. Formal descriptionsof syntax have been usually based either on the immediate constituents or on the dependency philosophy. Neither of them seems directly applicable to free word order languages. The intertwining phrases cannot be described naturally by IC rules. Some coordinate constructions are difficult to describe by means of dependency relations. In our opinion, parsers for free word order languages should not be based on the methods developed within the IC framework. Scarce experiments with parsers based on the dependency formalism, eg./5/, do not seem promising. Therefore, we decided to take a fresh start and to attack the problem by reanalys-ing the basic notions of syntax and parsing. We focus our attention on those formal aspects of a language system which might be most useful for automatic text processing. We assume that the morphological level is described along the lines of/2A "

word

order

term

term

syntax

based

constituents

dependency

free word order languages

phrases

rules

constructions

dependency relations

opinion

parsers

free word order languages

based

methods

developed

framework

experiments

parsers

based

dependency

formalism

problem

basic

notions

syntax

parsing

focus

aspects

language system

automatic

text processing

level

rules

phrases

methods

parsers

formalism

parsers

aspects

language system


Input: Logic Form Transformation Of WordNet And Its Applicability To Question Answering WordNet is a rich source of world knowledge from which formal axioms can be derived. In this paper we present a method for transforming the WordNet glosses into logic forms and further into axioms. The transformation of Word-Net glosses into logic forms is useful for theorem proving and other applications. The paper demonstrates the utility of the WordNet axioms in a question answering system to rank and extract answers.

source

world knowledge

axioms

paper

method

logic

forms

axioms

transformation

Word-

logic

forms

theorem

applications

paper

utility

axioms

question

system

rank

extract

axioms

source

paper

method

axioms

system


Input: Parsing Non-Recursive CFGs We consider the problem of parsing non-recursive context-free grammars, i. e., context-free grammars that generate finite languages. In natural language processing, this problem arises in several areas of application, including natural language generation, speech recognition and machine translation. We present two tabular algorithms for parsing ofnon-recursive context-free grammars, and show that they perform well in practical settings, despite the fact that this problem is PSPACE-complete.

problem

parsing

context-free

context-free

generate

languages

natural language processing

problem

areas

application

including

natural language generation

speech recognition

machine translation

algorithms

parsing

context-free

perform

problem

algorithms

parsing


Input: Massive Disambiguation Of Large Text Corpora With Flexible Categorial Grammar A new method of automatic lexical disambiguation of big texts is described, using recent proof-theoretical results from the theory of categorial grammar.

method

automatic

lexical

disambiguation

texts

results

theory

categorial grammar


Input: Using Constraints In A Constructive Version Of GPSG Complex categories are caracteristic of unification grammars as for example GPSG [Shieber86a]. They are sets of pairs of features and values. The unification, which can be applied to two or more categories, is the essential operation. The papers of [Shieber85], [Barton85] and [Ristad86] deal with the influence of complex categories on the efficiency of the parsing algorithm. This is one problem from using complex categories, another one arises when using a constructive version of GPSG (see [Busemann/Hauenschild88] in this volume). Namely that the application of admissibility conditions, e. g. LP statements and FCRs to m a local tree t is prevented because particular feature values of categories in t are not yet specified, but they will be instantiated later somewhere else in the complete tree. Similar problems are described. in [Karttunen86] for D-PATR. This work describes the latter problem and will present a solution working with computation, evaluation and propagation of constraints within local trees (depth 1). The constraint evaluation will reject local trees if the constraints of the subtrees of the daughters are violated.

Complex

categories

unification

example

pairs

features

unification

applied

categories

operation

papers

deal

influence

complex

categories

efficiency

parsing

algorithm

problem

complex

categories

version

volume

application

tree

feature values

categories

tree

problems

problem

solution

computation

evaluation

propagation

constraints

trees

constraint

evaluation

trees

constraints

feature values

categories


Input: Phonological Processing Of Speech Variants This paper describes a strategy for the extension of the phonological lexicon in order that nonstandard forms which arise in fast speech may be processed by a speech recognition system. By way of illustration, an outline of the phonological processing of standard wordforms by the phonological parser (PhoPa) is given and then the extension procedure which is based on this phonological parser is discussed. The lexicon extension procedure has two stages: phonotactic extension which involves the introduction of additional restrictions into the phonotactic network for the standard language in the form of metarules describing phonological processes, and specialised word model construction whereby for each standard phonemic wordform a verification net which contains all variants of this standard form is compiled. The complete system serves as a phonologically oriented lexicon development tool, and its theoretical interest lies in its contribution to the field of speech variant learning.

paper

strategy

extension

lexicon

order

forms

speech

processed

speech recognition system

outline

processing

standard

parser

extension

procedure

based

parser

lexicon

extension

procedure

extension

introduction

restrictions

network

standard

language

form

processes

word model

construction

standard

verification

variants

standard

form

system

lexicon

development

tool

contribution

field

speech

variant

learning

paper

strategy

speech recognition system

speech

parser

processing


Input: Zero Pronouns As Experiencer In Japanese Discourse The process of finding the antecedent of zero pronoun, that is indispensable to Japanese language understanding, is the topic of this paper. Here we mainly concern with discourses comprising two sentences that are in a subordinate relation, especially one of them describes the agent' s volitional action and the other describes the reason of the action. We propose basically two new principles: (1) The agent of an action should experience a certain psychological reason, (2) Predicates reporting someone' s psychological state are categorized into 1) weakly or 2) strongly bound to the expected point of view. Combination of these principles accounts for some problematic Japanese zero anaphora, which cannot be accounted for by the theories so far proposed.

process

Japanese

language understanding

topic

paper

concern

discourses

sentences

relation

agent

action

reason

action

propose

principles

agent

action

experience

reason

reporting

point of view

Combination

principles

Japanese

theories

proposed

paper

language understanding

sentences

discourses


Input: Tokenization As The Initial Phase In NLP In this paper, the authors address the significance and complexity of tokenization, the beginning step of NLP. Notions of word and token arc discussed and defined from the viewpoints of lexicography and pragmatic implementation, respectively. Automatic segmentation of Chinese words is presented as an illustration of tokenization. Practical approaches to identification of compound tokens in English, such as idioms, phrasal verbs and fixed expressions, are developed.

paper

significance

complexity

step

word

arc

implementation

Automatic

Chinese

words

approaches

identification

English

idioms

verbs

expressions

developed


Input: An English-To-Korean Machine Translator: MATES/EK This note introduces an EnglishKorean Machine Translation System MATES/EK, which has been de veloped as a research prototype and still under upgrading KAIST (Korea Advanced Institute of Science and Technology). MATES/EK a transfer-based system and has several subsystems that can be used support other-developments. They are grammar developing environment systems, dictionary developing tools, a set augmented context free grain mars English syntactic analysis, and so on.

note

Machine Translation System

research

prototype

Science

Technology

transfer-based system

support

developments

developing

environment

systems

dictionary

tools

context

mars

English

syntactic analysis


Input: Notes On LR Parser Design This paper discusses the design of an LR parser for a specific high-coverage English grammar. The design principles, though, are applicable to a large class of unification-based grammars where the constraints are realized as Prolog terms and applied monotonically through instantiation, where there is no right movement, and where left movement is handled by gap threading. The LR parser was constructed for experiments on probabilistic parsing and speedup learning, see [10]. LR parsers are suitable for probabilistic parsing since they contain a representation of the current parsing state, namely the stack and the input string, and since the actions of the parsing tables are easily attributed probabilities conditional on this parsing state. LR parsers are suitable for the speedup learning application since the learneu grammar is much larger than the original grammar, and the prefixes of the learned rules overlap to a very high degree, circumstances that are far from ideal for the system' s original parser. Even though these ends influenced the design of the parser, this article does not focus on these applications but rather on the design and testing of the parser itself.

paper

design

parser

high-coverage

English

design

principles

class

unification-based

constraints

terms

applied

gap

threading

parser

constructed

experiments

parsing

learning

parsers

parsing

representation

current

parsing

input

string

actions

parsing

tables

probabilities

parsing

parsers

application

prefixes

rules

degree

system

parser

influenced

design

parser

focus

applications

design

parser

paper

parser

parsers

parsing

parsers

application


Input: Towards Discourse-Oriented Nonmonotonic System The purpose of this paper is to analyse the phenomenon of nonmonotonicity in a natural language and to formulate a number of general principles which should be taken into consideration while constructing a discourse oriented nonmonotonic formalism.

purpose

paper

phenomenon

natural language

number

principles

consideration

constructing

discourse

formalism

paper

formalism


Input: Morphology And Cross Dependencies In The Synthesis Of Personal Pronouns In Romance Languages " This paper describes some of the problems that arise from the synthesis of personal pronouns in a system that generates texts in Romance languages. It puts the emphasis first on the fact that the morphological level has to be taken into account early in the generation process, second on the numerous " cross dependency " phenomena which are to be found when the synthesis of an element X depends upon that of another element Y and when the synthesis of Y depends upon that of X. The linguistic examples are taken from French and Italian languages, for which a robust generation system has been implemented. "

paper

problems

synthesis

system

generates

texts

languages

level

generation process

cross

dependency

phenomena

synthesis

synthesis

examples

languages

robust

generation system

implemented

examples

languages


Input: A News Analysis System This paper describes a prototype news analysis system which classifies and indexes news stories in real time. The system extracts stories from newswire, parses the sentences of the story, and then maps the syntactic structures into concept base. This process results in an index containing both general categories and specific details. Central to this system is a Government-Binding parser which processes each sentence of a news item. The system is completely modular and can be interfaced with different news feeds or concept bases.

paper

prototype

news

analysis

system

indexes

news

real time

system

extracts

parses

sentences

maps

syntactic structures

concept

base

process

results

index

categories

details

system

parser

processes

sentence

news

item

system

news

concept

bases

paper

system

base

syntactic structures

categories

index

parser

system

sentence

item


Input: Error Diagnosing And Selection In A Training System For Second Language Learning A diagnosing procedure to be used in intelligent systems for language instruction is presented. Based on a knowledge representation scheme for a certain class of syntactic correctness conditions the system carries out a thorough analysis of possible error hypotheses and their consequences. A comparison with earlier attempts shows a clearly improved precision of diagnostic results. First of all, the procedure concentrates on an exact localization of rule violations, but-if desired-is able to infer information about factual faults as well.

procedure

systems

language

instruction

Based

knowledge representation

scheme

class

syntactic

correctness

system

analysis

error

hypotheses

comparison

improved

precision

results

procedure

localization

rule

information

procedure

systems


Input: Tapping Huge Temporally Indexed Textual Resources with WCTAnalyze WCTAnalyze is a tool for storing, accessing and visually analyzing huge collections of temporally indexeddata. It is motivated by applications in media analysis, business intelligence etc. where higher level analysis is performed on top of linguistically and statistically processed unstructured textualdata. WCTAnalyze combines fast access with economically storage behaviour and appropriates a lot of built in visualization options for result presentation in detail as well as in contrast. So it enables an efficient and effective way to explore chronological text patterns of word forms, their co-occurrence sets and co-occurrence set intersections. Digging deep into co-occurrences of the same semantic or syntactic describing wordforms, some entities can be recognized as to be temporal related, whereas other differ significantly. This behaviour motivates approaches in interactive discovering events based on co-occurrence subsets.

tool

accessing

collections

indexeddata

indexeddata

applications

analysis

level

analysis

performed

processed

textualdata

access

storage

behaviour

visualization

options

result

presentation

detail

contrast

text

patterns

word

forms

co-occurrence

co-occurrence

intersections

semantic

syntactic

entities

behaviour

approaches

events

based

co-occurrence

indexeddata

collections

patterns

forms


Input: Linguistic Structure and Bilingual Informants Help Induce Machine Translation of Lesser-Resourced Languages Producing machine translation (MT) for the many minority languages in the world is a serious challenge. Minority languages typically have few resources for building MT systems. For many minor languages there is little machine readable text, few knowledgeable linguists, and little money available for MT development. For these reasons, our research programs on minority language MT have focused on leveraging to the maximum extent two resources that are available for minority languages: linguistic structure and bilingual informants. All natural languages contain linguistic structure. And although the details of that linguistic structure vary from language to language, language universals such as context-free syntactic structure and the paradigmatic structure of inflectional morphology, allow us to learn the specific details of a minority language. Similarly, most minority languages possess speakers who are bilingual with the major language of the area. This paper discusses our efforts to utilize linguistic structure and the translation information that bilingual informants can provide in three sub-areas of our rapid development MT program: morphology induction, syntactic transfer rule learning, and refinement of imperfect learned rules.

machine translation

languages

challenge

languages

resources

building

MT systems

languages

machine

text

linguists

development

reasons

research

programs

language

focused

leveraging

extent

resources

languages

linguistic structure

natural languages

linguistic structure

details

linguistic structure

language

language

language

context-free

syntactic structure

structure

morphology

details

language

languages

language

area

paper

efforts

linguistic structure

translation

information

provide

development

program

morphology

induction

syntactic

transfer

rule

learning

refinement

rules

machine translation

languages

linguistic structure

natural languages

paper

linguistic structure


Input: A Generative Model for Parsing Natural Language to Meaning Representations In this paper, we present an algorithm for learning a generative model of natural language sentences together with their formal meaning representations with hierarchical structures. The model is applied to the task of mapping sentences to hierarchical representations of their underlying meaning. We introduce dynamic programming techniques for efficient training and decoding. In experiments, we demonstrate that the model, when coupled with a discriminative reranking technique, achieves state-of-the-art performance when tested on two publicly available corpora. The generative model degrades robustly when presented with instances that are different from those seen in training. This allows a notable improvement in recall compared to previous models.

paper

algorithm

generative model

natural language sentences

meaning representations

hierarchical structures

model

applied

task

mapping

sentences

representations

dynamic programming

techniques

training

experiments

model

technique

performance

tested

corpora

generative model

instances

training

improvement

recall

models

paper

algorithm

meaning representations

natural language sentences

model

mapping

model

performance


Input: A Comparative Study on Language Identification Methods In this paper we present two experiments conducted for comparison of different language identification algorithms. Short words-, frequent words-and n-gram-based approaches are considered and combined with the Ad-Hoc Ranking classification method. The language identification process can be subdivided into two main steps: First a document model is generated for the document and a language model for the language; second the language of the document is determined on the basis of the language model and is added to the document as additional information. In this work we present our evaluation results and discuss the importance of a dynamic value for the out-of-place measure.

paper

experiments

comparison

language

identification

algorithms

words-

words-

n-gram-based approaches

classification

method

language

identification

process

main

steps

document

model

generated

document

language model

language

language

document

basis

language model

document

information

evaluation results

importance

paper

experiments

model

document

language model

language


Input: QUALIFIER: Question Answering By Lexical Fabric And External Resources One of the major challenges in TREC-style question-answering (QA) is to overcome the mismatch in the lexical representations in the query space and document space. This is particularly severe in QA as exact answers, rather than documents, are required in response to questions. Most current approaches overcome the mismatch problem by employing eitherdata redundancy strategy through the use of Web or linguistic resources. This paper investigates the integration of lexical relations and Web knowledge to tackle this problem. The results obtained on TREC11 QA corpus indicate that our approach is both feasible and effective.

challenges

question-answering

mismatch

lexical

representations

query

space

document

space

documents

required

questions

current

approaches

mismatch

problem

eitherdata

redundancy

strategy

linguistic resources

paper

integration

lexical

relations

knowledge

problem

results

corpus

approach

mismatch

representations


Input: CALL: The Potential Of LINGWARE And The Use Of Empirical Linguistic Data Language technology has significantly evolved during the last decade. However, the community of language learning seems to ignore this development, most of the existing language learning systems drawing their enhancements from other sources, such as hypertext, multimedia, interactive video, information retrieval. Despite some spectacular progress made at the level of interface, several fundamental language learning principles, are only partially met. Nevertheless, the hypermedia technology did solve one very important aspect of computer-assisted learning by putting the student in a visual environment. Minimizing cultural differences they' ve been able to draw on shared background knowledge (microworld immersiveness). Other important aspects of typical immersion-based approaches, i. e. natural learning, such as mixed-initiative, fault-tolerance, dialogue repair, cooperative behaviour, etc. are still in their infancy. In real settings learners freely interact with their environment (parents, tutors), taking turns, asking for explanations, shifting topics, etc. The language produced by the learner is more often than not agrammatical, yet this does not prevent the tutor to proceed with the dialog. Error correction is usually done contextually, by drawing either explicitly attention to the deviation, by producing a similar but correct sentence, or by simply ignoring the mistake leaving its correction for later. There are many AI and CL programs solving various specific CALL-relevant problems. If assembled properly, these pieces could result in very powerful language learning systems. Lexical thesauri Parsers Generators Semantic interpreters/generators

Language technology

community

language

development

language

systems

enhancements

sources

hypertext

video

information retrieval

progress

level

interface

language

principles

technology

solve

aspect

computer-assisted

learning

environment

differences

background knowledge

aspects

immersion-based approaches

natural

learning

mixed-initiative

dialogue

repair

behaviour

environment

explanations

shifting

topics

language

dialog

Error

correction

deviation

sentence

correction

programs

solving

CALL-relevant

problems

result

language

systems

Lexical

thesauri

Semantic

interpreters

generators


Input: Named Entity Chunking Techniques In Supervised Learning For Japanese Named Entity Recognition This paper focuses on the issue of named entity chunking in Japanese named entity recognition. We apply the supervised decision list learning method to Japanese named entity recognition. We also investigate and incorporate several named-entity noun phrase chunking techniques and experimentally evaluate and compare their performance. In addition, we propose a method for incorporating richer contextual information as well as patterns of constituent morphemes within a named entity, which have not been considered in previous research, and show that the proposed method outperforms these previous approaches.

paper

focuses

issue

named

entity

chunking

Japanese

named

entity

recognition

apply

decision

list

method

Japanese

named

entity

recognition

named-entity

noun phrase

chunking

techniques

evaluate

performance

addition

propose

method

contextual information

patterns

constituent

named

entity

research

proposed

method

approaches

paper

chunking

method

recognition


Input: An Inference-Based Approach To Dialogue System Design We present an architecture for spoken dialogue systems where first-order inference (both theorem proving and model building) plays a crucial role in interpreting utterances of dialogue participants and deciding how the system should respond and carry out instructions. The dialogue itself is represented SIS St DRS which is translated into first-order logic for inference tasks. The system is implemented SIS St society of OAA-agents, and evaluated against a specific application (home automation).

architecture

dialogue systems

first-order

inference

theorem

model

building

role

utterances

dialogue

participants

system

instructions

dialogue

SIS

translated

first-order

logic

inference

tasks

system

implemented

SIS

evaluated

application

automation


Input: Compilation Of Unification Grammars With Compositional Semantics To Speech Recognition Packages In this paper a method to compile unification grammars into speech recognition packages is presented, and in particular, rules are specified to transfer the compositional semantics stated in unification grammars into speech recognition grammars. The resulting compiler creates a context-free backbone of the unification grammar, eliminates left-recursive productions and removes redundant grammar rules. The method was tested on a medium-sized unification grammar for English using Nuance speech recognition software on a corpus of 131 utterances of 12 different speakers. Results showed no significant computational overhead with respect to speech recognition performances for speech recognition grammar with compositional semantics compared to grammars without.

paper

method

unification

speech recognition

packages

rules

transfer

semantics

unification

speech recognition

resulting

context-free

backbone

unification

grammar rules

method

tested

unification

English

speech recognition

software

corpus

utterances

Results

computational

respect

speech recognition

performances

speech recognition

semantics

paper

method

method

English

software

corpus


Input: Feature Weighting For Co-Occurrence-Based Classification Of Words The paper comparatively studies methods of feature weighting in application to the task of cooccurrence-based classification of words according to their meaning. We explore parameter optimization of several weighting methods frequently used for similar problems such as text classification. We find that successful application of all the methods crucially depends on a number of parameters; only a carefully chosen weighting procedure allows to obtain consistent improvement on a classifier learned from non-weighteddata.

paper

studies

methods

feature

weighting

application

task

classification

words

parameter

optimization

weighting

methods

problems

text classification

application

methods

number

parameters

weighting

procedure

improvement

classifier

weighteddata

paper

methods

classification

words


Input: Trajectory Based Word Sense Disambiguation Classifier combination is a promising way to improve performance of word sense disambiguation. We propose a new combinational method in this paper. We first construct a series of Na ve Bayesian classifiers along a sequence of orderly varying sized windows of context, and perform sense selection for both training samples and test samples using these classifiers. We thus get a sense selection trajectory along the sequence of context windows for each sample. Then we make use of these trajectories to make final k-nearest-neighbors-based sense selection for test samples. This method aims to lower the uncertainty brought by classifiers using different context windows and make more robust utilization of context while perform well. Experiments show that our approach outperforms some other algorithms on both robustness and performance.

Classifier

combination

improve

performance

word sense disambiguation

propose

method

paper

construct

series

classifiers

sequence

sized

windows

context

perform

sense

selection

training

samples

test

samples

classifiers

sense

selection

sequence

context

windows

sample

sense

selection

test

samples

method

uncertainty

classifiers

context

windows

robust

context

perform

Experiments

approach

algorithms

robustness

performance

paper

method

classifiers

selection

windows

method


Input: Automated Induction Of Sense In Context In this paper, we introduce a model for sense assignment which relies on assigning senses to the contexts within which words appear, rather than to the words themselves. We argue that word senses as such are not directly encoded in the lexicon of the language. Rather, each word is associated with one or more stereotypical syntagmatic patterns, which we call selection contexts.

paper

model

sense

assignment

contexts

words

words

word

lexicon

language

word

patterns

call

selection

contexts

paper

model

contexts

assignment


Input: Situations And Prepositional Phrases This paper presents a format for representing the linguistic form of utterances, called situation schemata, which is rooted in the situation semantics of Barwise and Perry. A treatment of locative prepositional phrases is given, thus illustrating the generation of the situation schemata and their interpretation in situation semantics.

paper

format

form

utterances

called

situation

schemata

situation

semantics

treatment

prepositional phrases

generation

situation

schemata

interpretation

situation

semantics

paper

format

form

utterances

interpretation

schemata


Input: The U. S. Policy Agenda Legislation Corpus Volume 1-a Language Resource from 1947-1998 We introduce the corpus of United States Congressional bills from 1947 to 1998 for use by language research communities. The U. S. Policy Agenda Legislation Corpus Volume 1 (USPALCV1) includes more than 375, 000 legislative bills annotated with a hierarchical policy area category. The human annotations in USPALCV1 have been reliably applied over time to enable social science analysis of legislative trends. The corpus is a member of an emerging family of corpora that are annotated by policy area to enable comparative parallel trend recognition across countries and domains (legislation, political speeches, newswire articles, budgetary expenditures, web sites, etc.). This paper describes the origins of the corpus, its creation, ways to access it, design criteria, and an analysis with common supervised machine learning methods. The use of machine learning methods establishes a baseline proposed modeling for the topic classification of legal documents.

corpus

language

research

communities

Agenda

Corpus

Volume

includes

area

category

applied

time

science

analysis

trends

corpus

corpora

area

trend

recognition

domains

speeches

web sites

paper

corpus

creation

access

design

criteria

analysis

common

machine

methods

machine

methods

proposed

modeling

topic

classification

documents

corpus

research

corpus

corpora

paper

corpus

classification

documents


Input: JMWNL: an Extensible Multilingual Library for Accessing Wordnets in Different Languages In this paper we present JMWNL, a multilingual extension of the JWNL java library, which was originally developed for accessing Princeton WordNet dictionaries. JMWNL broadens the range of JWNL' s accessible resources by covering also dictionaries produced inside the EuroWordNet project. Specific resources, such as language-dependent algorithmic stemmers, have been adopted to cover the diversities in the morphological nature of words in the addressed idioms. New semantic and lexical relations have been included to maximize compatibility with new versions of the original Princeton WordNet and to include the whole range of relations from EuroWordNet. Relations from Princeton WordNet on one side and EuroWordNet on the other one have in some cases been mapped to provide a uniform reference for coherent cross-linguistic use of the library.

paper

extension

library

developed

accessing

dictionaries

resources

dictionaries

project

resources

language-dependent

diversities

nature

words

idioms

semantic

lexical

relations

included

compatibility

versions

include

relations

Relations

side

cases

mapped

provide

reference

cross-linguistic

library

paper

extension

diversities

words


Input: Methodology for Evaluating the Usability of User Interfaces in Mobile Services In this paper we present a usability measure adapted to mobile services, which is based on the well-known theoretical framework defined in the ISO 9241-11 [ISO 9241 (1988)] standard. This measure is then applied to a representative set of services of the Telefonica' s portfolio for residential customers. The user tests that we present were carried out by a total of 327 people. Additionally, in section 3 we describe the application of the methodology to a particular service and section 4 presents the results of the experiments. These results show highly significant differences in the three usability measures considered, though all of them have the same trend. The worst performers in all cases were the WAP and i-mode user interfaces (UI), while the best performers were the SMS and web based UIs closely followed by the voice UI. Finally, in section 5 we analyse the results and present our conclusions.

paper

adapted

based

framework

standard

applied

representative

customers

user

tests

section

application

methodology

section

results

experiments

results

differences

trend

cases

i-mode

user interfaces

based

section

results

conclusions

experiments

results


Input: The 2008 Oriental COCOSDA Book Project: in Commemoration of the First Decade of Sustained Activities in Asia The purpose of Oriental COCOSDA is to provide the Asian community a platform to exchange ideas, to share information and to discuss regional matters on creation, utilization, dissemination of spoken language corpora of oriental languages and also on the assessment methods of speech recognition/synthesis systems as well as to promote speech research on oriental languages. Since its preparatory meeting in Hong Kong in 1997, annual workshops have been organized and held in Japan, Taiwan, China, Korea, Thailand, Singapore, India, Indonesia, Malaysia, and Vietnam from 1998. The organization is managed by a convener, three advisory members, and 26 committee members from 13 regions in Oriental area. In order to commemorate 10 years of continued activities, the members have decided to publish a book which covers a wide range of speech research. Special focus will be on speech resources or speech corpora in Oriental countries and standardization of speech input/output systems performance evaluation methods on which key technologies for speech systems development are based. The book will also include linguistic outlines of oriental languages, annotation, labeling, and software tools for speech processing.

purpose

provide

community

platform

information

creation

language

corpora

languages

assessment

methods

speech recognition

synthesis

systems

speech

research

languages

meeting

Hong

workshops

organization

regions

area

order

speech

research

focus

speech

resources

speech corpora

speech

input

output

systems

performance

evaluation methods

technologies

speech

systems

development

based

include

outlines

languages

software

tools

speech processing

languages

corpora

methods

assessment

tools

speech processing


Input: A CD-ROM Retrieval System With Multiple Dialogue Agents In this paper, we proposed a new dialogue system with multiple dialogue agents. In our new system, three types of agents: a) domain agents, b) strategy agents, and c) context agents were realized. They give the following advantages to the user: the domain agents make the user aware of the boundary between the domains. the strategy agents make the user aware of the difference between the strategies. the context agents help the user to deal with multiple goals. We expect that the complex behaviors of the system will become more visible to the user in different situations. The experimental results show that the user can retrieve effectively and obtain the expected goals easily by using these multiple agents.

paper

proposed

dialogue system

dialogue

agents

system

types

agents

domain

agents

strategy

agents

context

agents

advantages

user

domain

agents

user

boundary

domains

strategy

agents

user

difference

strategies

context

agents

help

user

deal

goals

complex

behaviors

system

user

situations

experimental

results

user

goals

agents

paper

dialogue system


Input: Computation Of Relative Social Status On The Basis Of Honorification In Korean This paper presents a way to compute relative social status of the individuals involved in Korean dialogue. Every Korean sentence indicates whether honorification occurs in it. The occurrence of honorification in a sentence is constr ained by relative social status of the individuals involved in the sentence. By using the information about social status and the information about sentence-external individuals such as speaker and addressee, we can explain why a sentence is felicitous in a restricted context and whether a dialogue is coherent or not. Since it is possible and easy to include such contextual information in the HPSG formalism, that formalism is adopted here. The implementation of Korean dialogue processing and the computation of social status is made based on ALE system.

paper

compute

relative

status

individuals

dialogue

sentence

occurrence

sentence

relative

status

individuals

sentence

information

status

information

sentence-external

individuals

sentence

context

dialogue

include

contextual information

formalism

formalism

implementation

dialogue

processing

computation

status

based

system

contextual information

formalism

processing

dialogue


Input: Learning Part-Of-Speech Guessing Rules From Lexicon: Extension To Non-Concatenative Operations One of the problems in part-of-speech tagging of real-word texts is that of unknown to the lexicon words. In (Mikheev, 1996), a technique for fully unsupervised statistical acquisition of rules which guess possible parts-of-speech for unknown words was proposed. One of the over-simplification assumed by this learning technique was the acquisition of morphological rules which obey only simple concatenative regularities of the main word with an affix. In this paper wc extend this technique to the non-concatenative cases of suffixation and assess the gain in the performance.

problems

part-of-speech

tagging

real-word

texts

lexicon

words

technique

statistical

acquisition

rules

parts-of-speech

unknown words

proposed

over-simplification

technique

acquisition

rules

simple

regularities

main

word

paper

technique

cases

gain

performance

tagging

texts

technique

acquisition

parts-of-speech

unknown words

paper

technique


Input: An Efficient Execution Method For Rule-Based Machine Translation A rule based system is an effective way to implement a machine translation system because of its extensibility and maintainability. However, it is disadvantageous in processing efficiency. In a rule based machine translation system, the grammar consists of a lot of rewriting rules. While the translation is carried out by repeating pattern matching and transformation of graph structures, most rules fail in pattern matching. It is to be desired that pattern matching of the unfruitful rules should be avoided. This paper proposes a method to restrict the rule application by activating rules dynamically. The logical relationship among rules are pre-analyzed and a set of antecedent actions, which are prerequisite for the condition of the rule being satisfied, is determined for each rule. In execution time, a rule is activated only when one of the antecedent actions are carried out. The probability of a rule being activated is reduced to near the occurrence probability of its relevant linguistic phenomenon. As most rules relate to linguistic phenomena that rarely occur, the processing efficiency is drastically improved.

rule

based

system

implement

machine translation system

processing

efficiency

rule

based

machine translation system

rules

translation

pattern matching

transformation

structures

rules

pattern matching

pattern matching

rules

paper

proposes

method

rule application

rules

relationship

rules

actions

rule

rule

execution

time

rule

actions

probability

rule

occurrence

probability

phenomenon

rules

phenomena

processing

efficiency

improved

system

machine translation system

rules

machine translation system

paper

method

probability

rule

probability

phenomenon

rules

phenomena


Input: Hopfield Models As Nondeterministic Finite-State Machines The use of neural networks for integrated linguistic analysis may be profitable. This paper presents the first results of our research on that subject: a Hop-field model for syntactical analysis. We construct a neural network as an implementation of a bounded push-down automaton, which can accept context-free languages with limited center-embedding. The network' s behavior can be predicted a priori, so the presented theory can be tested. The operation of the network as an implementation of the acceptor is prov-ably correct. Furthermore we found a solution to the problem of spurious states in Hopfield models: we use them as dynamically constructed representations of sets of states of the implemented acceptor. The so-called neural-network acceptor we propose, is fast but large.

Models

neural networks

linguistic analysis

paper

results

research

Hop-field

model

analysis

construct

neural network

implementation

context-free

languages

center-embedding

network

behavior

theory

tested

operation

network

implementation

solution

problem

models

constructed

representations

implemented

neural-network

propose

neural networks

linguistic analysis

model

analysis


Input: Generation Of Accent In Nominally Premodified Noun Phrases The primary purpose of this paper is to present a set of conditions that constrain accent placement in focused nominally premodified Selkirk (1984) argues that if the premodifier is an argument of the head, then the head can be deaccented. I agree with Selkirk' s proposal and argue that what essential is not whether the premodifier is a grammatical argument of the head noun, but rather, whether it is a 6-complement in lexical conceptual structure. This proposal is evaluated by testing it against a corpus of naturally occurringdata.

purpose

paper

focused

argument

proposal

argument

noun

complement

lexical

conceptual structure

proposal

evaluated

testing

corpus

occurringdata

occurringdata

corpus