Datasets:
Titles
stringlengths 6
220
| Abstracts
stringlengths 37
3.26k
| Years
int64 1.99k
2.02k
| Categories
stringclasses 1
value |
|---|---|---|---|
Introduction to Arabic Speech Recognition Using CMUSphinx System | In this paper Arabic was investigated from the speech recognition problem
point of view. We propose a novel approach to build an Arabic Automated Speech
Recognition System (ASR). This system is based on the open source CMU Sphinx-4,
from the Carnegie Mellon University. CMU Sphinx is a large-vocabulary;
speaker-independent, continuous speech recognition system based on discrete
Hidden Markov Models (HMMs). We build a model using utilities from the
OpenSource CMU Sphinx. We will demonstrate the possible adaptability of this
system to Arabic voice recognition.
| 2,007 | Computation and Language |
Arabic Speech Recognition System using CMU-Sphinx4 | In this paper we present the creation of an Arabic version of Automated
Speech Recognition System (ASR). This system is based on the open source
Sphinx-4, from the Carnegie Mellon University. Which is a speech recognition
system based on discrete hidden Markov models (HMMs). We investigate the
changes that must be made to the model to adapt Arabic voice recognition.
Keywords: Speech recognition, Acoustic model, Arabic language, HMMs,
CMUSphinx-4, Artificial intelligence.
| 2,007 | Computation and Language |
On the Development of Text Input Method - Lessons Learned | Intelligent Input Methods (IM) are essential for making text entries in many
East Asian scripts, but their application to other languages has not been fully
explored. This paper discusses how such tools can contribute to the development
of computer processing of other oriental languages. We propose a design
philosophy that regards IM as a text service platform, and treats the study of
IM as a cross disciplinary subject from the perspectives of software
engineering, human-computer interaction (HCI), and natural language processing
(NLP). We discuss these three perspectives and indicate a number of possible
future research directions.
| 2,007 | Computation and Language |
Network statistics on early English Syntax: Structural criteria | This paper includes a reflection on the role of networks in the study of
English language acquisition, as well as a collection of practical criteria to
annotate free-speech corpora from children utterances. At the theoretical
level, the main claim of this paper is that syntactic networks should be
interpreted as the outcome of the use of the syntactic machinery. Thus, the
intrinsic features of such machinery are not accessible directly from (known)
network properties. Rather, what one can see are the global patterns of its use
and, thus, a global view of the power and organization of the underlying
grammar. Taking a look into more practical issues, the paper examines how to
build a net from the projection of syntactic relations. Recall that, as opposed
to adult grammars, early-child language has not a well-defined concept of
structure. To overcome such difficulty, we develop a set of systematic criteria
assuming constituency hierarchy and a grammar based on lexico-thematic
relations. At the end, what we obtain is a well defined corpora annotation that
enables us i) to perform statistics on the size of structures and ii) to build
a network from syntactic relations over which we can perform the standard
measures of complexity. We also provide a detailed example.
| 2,007 | Computation and Language |
Segmentation and Context of Literary and Musical Sequences | We test a segmentation algorithm, based on the calculation of the
Jensen-Shannon divergence between probability distributions, to two symbolic
sequences of literary and musical origin. The first sequence represents the
successive appearance of characters in a theatrical play, and the second
represents the succession of tones from the twelve-tone scale in a keyboard
sonata. The algorithm divides the sequences into segments of maximal
compositional divergence between them. For the play, these segments are related
to changes in the frequency of appearance of different characters and in the
geographical setting of the action. For the sonata, the segments correspond to
tonal domains and reveal in detail the characteristic tonal progression of such
kind of musical composition.
| 2,007 | Computation and Language |
International Standard for a Linguistic Annotation Framework | This paper describes the Linguistic Annotation Framework under development
within ISO TC37 SC4 WG1. The Linguistic Annotation Framework is intended to
serve as a basis for harmonizing existing language resources as well as
developing new ones.
| 2,004 | Computation and Language |
A Formal Model of Dictionary Structure and Content | We show that a general model of lexical information conforms to an abstract
model that reflects the hierarchy of information found in a typical dictionary
entry. We show that this model can be mapped into a well-formed XML document,
and how the XSL transformation language can be used to implement a semantics
defined over the abstract model to enable extraction and manipulation of the
information in any format.
| 2,000 | Computation and Language |
Practical Approach to Knowledge-based Question Answering with Natural
Language Understanding and Advanced Reasoning | This research hypothesized that a practical approach in the form of a
solution framework known as Natural Language Understanding and Reasoning for
Intelligence (NaLURI), which combines full-discourse natural language
understanding, powerful representation formalism capable of exploiting
ontological information and reasoning approach with advanced features, will
solve the following problems without compromising practicality factors: 1)
restriction on the nature of question and response, and 2) limitation to scale
across domains and to real-life natural language text.
| 2,007 | Computation and Language |
Learning Probabilistic Models of Word Sense Disambiguation | This dissertation presents several new methods of supervised and unsupervised
learning of word sense disambiguation models. The supervised methods focus on
performing model searches through a space of probabilistic models, and the
unsupervised methods rely on the use of Gibbs Sampling and the Expectation
Maximization (EM) algorithm. In both the supervised and unsupervised case, the
Naive Bayesian model is found to perform well. An explanation for this success
is presented in terms of learning rates and bias-variance decompositions.
| 1,998 | Computation and Language |
Learning Phonotactics Using ILP | This paper describes experiments on learning Dutch phonotactic rules using
Inductive Logic Programming, a machine learning discipline based on inductive
logical operators. Two different ways of approaching the problem are
experimented with, and compared against each other as well as with related work
on the task. The results show a direct correspondence between the quality and
informedness of the background knowledge and the constructed theory,
demonstrating the ability of ILP to take good advantage of the prior domain
knowledge available. Further research is outlined.
| 2,002 | Computation and Language |
Bootstrapping Deep Lexical Resources: Resources for Courses | We propose a range of deep lexical acquisition methods which make use of
morphological, syntactic and ontological language resources to model word
similarity and bootstrap from a seed lexicon. The different methods are
deployed in learning lexical items for a precision grammar, and shown to each
have strengths and weaknesses over different word classes. A particular focus
of this paper is the relative accessibility of different language resource
types, and predicted ``bang for the buck'' associated with each in deep lexical
acquisition applications.
| 2,005 | Computation and Language |
Bio-linguistic transition and Baldwin effect in an evolutionary
naming-game model | We examine an evolutionary naming-game model where communicating agents are
equipped with an evolutionarily selected learning ability. Such a coupling of
biological and linguistic ingredients results in an abrupt transition: upon a
small change of a model control parameter a poorly communicating group of
linguistically unskilled agents transforms into almost perfectly communicating
group with large learning abilities. When learning ability is kept fixed, the
transition appears to be continuous. Genetic imprinting of the learning
abilities proceeds via Baldwin effect: initially unskilled communicating agents
learn a language and that creates a niche in which there is an evolutionary
pressure for the increase of learning ability.Our model suggests that when
linguistic (or cultural) processes became intensive enough, a transition took
place where both linguistic performance and biological endowment of our species
experienced an abrupt change that perhaps triggered the rapid expansion of
human civilization.
| 2,008 | Computation and Language |
Zipf's Law and Avoidance of Excessive Synonymy | Zipf's law states that if words of language are ranked in the order of
decreasing frequency in texts, the frequency of a word is inversely
proportional to its rank. It is very robust as an experimental observation, but
to date it escaped satisfactory theoretical explanation. We suggest that Zipf's
law may arise from the evolution of word semantics dominated by expansion of
meanings and competition of synonyms.
| 2,008 | Computation and Language |
On the role of autocorrelations in texts | The task of finding a criterion allowing to distinguish a text from an
arbitrary set of words is rather relevant in itself, for instance, in the
aspect of development of means for internet-content indexing or separating
signals and noise in communication channels. The Zipf law is currently
considered to be the most reliable criterion of this kind [3]. At any rate,
conventional stochastic word sets do not meet this law. The present paper deals
with one of possible criteria based on the determination of the degree of data
compression.
| 2,007 | Computation and Language |
On the fractal nature of mutual relevance sequences in the Internet news
message flows | In the task of information retrieval the term relevance is taken to mean
formal conformity of a document given by the retrieval system to user's
information query. As a rule, the documents found by the retrieval system
should be submitted to the user in a certain order. Therefore, a retrieval
perceived as a selection of documents formally solving the user's query, should
be supplemented with a certain procedure of processing a relevant set. It would
be natural to introduce a quantitative measure of document conformity to query,
i.e. the relevance measure. Since no single rule exists for the determination
of the relevance measure, we shall consider two of them which are the simplest
in our opinion. The proposed approach does not suppose any restrictions and can
be applied to other relevance measures.
| 2,007 | Computation and Language |
What's in a Name? | This paper describes experiments on identifying the language of a single name
in isolation or in a document written in a different language. A new corpus has
been compiled and made available, matching names against languages. This corpus
is used in a series of experiments measuring the performance of general
language models and names-only language models on the language identification
task. Conclusions are drawn from the comparison between using general language
models and names-only language models and between identifying the language of
isolated names and the language of very short document fragments. Future
research directions are outlined.
| 2,007 | Computation and Language |
The structure of verbal sequences analyzed with unsupervised learning
techniques | Data mining allows the exploration of sequences of phenomena, whereas one
usually tends to focus on isolated phenomena or on the relation between two
phenomena. It offers invaluable tools for theoretical analyses and exploration
of the structure of sentences, texts, dialogues, and speech. We report here the
results of an attempt at using it for inspecting sequences of verbs from French
accounts of road accidents. This analysis comes from an original approach of
unsupervised training allowing the discovery of the structure of sequential
data. The entries of the analyzer were only made of the verbs appearing in the
sentences. It provided a classification of the links between two successive
verbs into four distinct clusters, allowing thus text segmentation. We give
here an interpretation of these clusters by applying a statistical analysis to
independent semantic annotations.
| 2,007 | Computation and Language |
Linguistic Information Energy | In this treatment a text is considered to be a series of word impulses which
are read at a constant rate. The brain then assembles these units of
information into higher units of meaning. A classical systems approach is used
to model an initial part of this assembly process. The concepts of linguistic
system response, information energy, and ordering energy are defined and
analyzed. Finally, as a demonstration, information energy is used to estimate
the publication dates of a series of texts and the similarity of a set of
texts.
| 2,007 | Computation and Language |
Generating models for temporal representations | We discuss the use of model building for temporal representations. We chose
Polish to illustrate our discussion because it has an interesting aspectual
system, but the points we wish to make are not language specific. Rather, our
goal is to develop theoretical and computational tools for temporal model
building tasks in computational semantics. To this end, we present a
first-order theory of time and events which is rich enough to capture
interesting semantic distinctions, and an algorithm which takes minimal models
for first-order theories and systematically attempts to ``perturb'' their
temporal component to provide non-minimal, but semantically significant,
models.
| 2,007 | Computation and Language |
Using Description Logics for Recognising Textual Entailment | The aim of this paper is to show how we can handle the Recognising Textual
Entailment (RTE) task by using Description Logics (DLs). To do this, we propose
a representation of natural language semantics in DLs inspired by existing
representations in first-order logic. But our most significant contribution is
the definition of two novel inference tasks: A-Box saturation and subgraph
detection which are crucial for our approach to RTE.
| 2,007 | Computation and Language |
Using Synchronic and Diachronic Relations for Summarizing Multiple
Documents Describing Evolving Events | In this paper we present a fresh look at the problem of summarizing evolving
events from multiple sources. After a discussion concerning the nature of
evolving events we introduce a distinction between linearly and non-linearly
evolving events. We present then a general methodology for the automatic
creation of summaries from evolving events. At its heart lie the notions of
Synchronic and Diachronic cross-document Relations (SDRs), whose aim is the
identification of similarities and differences between sources, from a
synchronical and diachronical perspective. SDRs do not connect documents or
textual elements found therein, but structures one might call messages.
Applying this methodology will yield a set of messages and relations, SDRs,
connecting them, that is a graph which we call grid. We will show how such a
grid can be considered as the starting point of a Natural Language Generation
System. The methodology is evaluated in two case-studies, one for linearly
evolving events (descriptions of football matches) and another one for
non-linearly evolving events (terrorist incidents involving hostages). In both
cases we evaluate the results produced by our computational systems.
| 2,007 | Computation and Language |
Some Reflections on the Task of Content Determination in the Context of
Multi-Document Summarization of Evolving Events | Despite its importance, the task of summarizing evolving events has received
small attention by researchers in the field of multi-document summariztion. In
a previous paper (Afantenos et al. 2007) we have presented a methodology for
the automatic summarization of documents, emitted by multiple sources, which
describe the evolution of an event. At the heart of this methodology lies the
identification of similarities and differences between the various documents,
in two axes: the synchronic and the diachronic. This is achieved by the
introduction of the notion of Synchronic and Diachronic Relations. Those
relations connect the messages that are found in the documents, resulting thus
in a graph which we call grid. Although the creation of the grid completes the
Document Planning phase of a typical NLG architecture, it can be the case that
the number of messages contained in a grid is very large, exceeding thus the
required compression rate. In this paper we provide some initial thoughts on a
probabilistic model which can be applied at the Content Determination stage,
and which tries to alleviate this problem.
| 2,007 | Computation and Language |
Discriminative Phoneme Sequences Extraction for Non-Native Speaker's
Origin Classification | In this paper we present an automated method for the classification of the
origin of non-native speakers. The origin of non-native speakers could be
identified by a human listener based on the detection of typical pronunciations
for each nationality. Thus we suppose the existence of several phoneme
sequences that might allow the classification of the origin of non-native
speakers. Our new method is based on the extraction of discriminative sequences
of phonemes from a non-native English speech database. These sequences are used
to construct a probabilistic classifier for the speakers' origin. The existence
of discriminative phone sequences in non-native speech is a significant result
of this work. The system that we have developed achieved a significant correct
classification rate of 96.3% and a significant error reduction compared to some
other tested techniques.
| 2,007 | Computation and Language |
Combined Acoustic and Pronunciation Modelling for Non-Native Speech
Recognition | In this paper, we present several adaptation methods for non-native speech
recognition. We have tested pronunciation modelling, MLLR and MAP non-native
pronunciation adaptation and HMM models retraining on the HIWIRE foreign
accented English speech database. The ``phonetic confusion'' scheme we have
developed consists in associating to each spoken phone several sequences of
confused phones. In our experiments, we have used different combinations of
acoustic models representing the canonical and the foreign pronunciations:
spoken and native models, models adapted to the non-native accent with MAP and
MLLR. The joint use of pronunciation modelling and acoustic adaptation led to
further improvements in recognition accuracy. The best combination of the above
mentioned techniques resulted in a relative word error reduction ranging from
46% to 71%.
| 2,007 | Computation and Language |
Am\'elioration des Performances des Syst\`emes Automatiques de
Reconnaissance de la Parole pour la Parole Non Native | In this article, we present an approach for non native automatic speech
recognition (ASR). We propose two methods to adapt existing ASR systems to the
non-native accents. The first method is based on the modification of acoustic
models through integration of acoustic models from the mother tong. The
phonemes of the target language are pronounced in a similar manner to the
native language of speakers. We propose to combine the models of confused
phonemes so that the ASR system could recognize both concurrent
pronounciations. The second method we propose is a refinment of the
pronounciation error detection through the introduction of graphemic
constraints. Indeed, non native speakers may rely on the writing of words in
their uttering. Thus, the pronounctiation errors might depend on the characters
composing the words. The average error rate reduction that we observed is
(22.5%) relative for the sentence error rate, and 34.5% (relative) in word
error rate.
| 2,007 | Computation and Language |
Can a Computer Laugh ? | A computer model of "a sense of humour" suggested previously
[arXiv:0711.2058,0711.2061], relating the humorous effect with a specific
malfunction in information processing, is given in somewhat different
exposition. Psychological aspects of humour are elaborated more thoroughly. The
mechanism of laughter is formulated on the more general level. Detailed
discussion is presented for the higher levels of information processing, which
are responsible for a perception of complex samples of humour. Development of a
sense of humour in the process of evolution is discussed.
| 1,994 | Computation and Language |
Proof nets for display logic | This paper explores several extensions of proof nets for the Lambek calculus
in order to handle the different connectives of display logic in a natural way.
The new proof net calculus handles some recent additions to the Lambek
vocabulary such as Galois connections and Grishin interactions. It concludes
with an exploration of the generative capacity of the Lambek-Grishin calculus,
presenting an embedding of lexicalized tree adjoining grammars into the
Lambek-Grishin calculus.
| 2,007 | Computation and Language |
How to realize "a sense of humour" in computers ? | Computer model of a "sense of humour" suggested previously [arXiv:0711.2058,
0711.2061, 0711.2270] is raised to the level of a realistic algorithm.
| 2,007 | Computation and Language |
Morphological annotation of Korean with Directly Maintainable Resources | This article describes an exclusively resource-based method of morphological
annotation of written Korean text. Korean is an agglutinative language. Our
annotator is designed to process text before the operation of a syntactic
parser. In its present state, it annotates one-stem words only. The output is a
graph of morphemes annotated with accurate linguistic information. The
granularity of the tagset is 3 to 5 times higher than usual tagsets. A
comparison with a reference annotated corpus showed that it achieves 89% recall
without any corpus training. The language resources used by the system are
lexicons of stems, transducers of suffixes and transducers of generation of
allomorphs. All can be easily updated, which allows users to control the
evolution of the performances of the system. It has been claimed that
morphological annotation of Korean text could only be performed by a
morphological analysis module accessing a lexicon of morphemes. We show that it
can also be performed directly with a lexicon of words and without applying
morphological rules at annotation time, which speeds up annotation to 1,210
word/s. The lexicon of words is obtained from the maintainable language
resources through a fully automated compilation process.
| 2,006 | Computation and Language |
Lexicon management and standard formats | International standards for lexicon formats are in preparation. To a certain
extent, the proposed formats converge with prior results of standardization
projects. However, their adequacy for (i) lexicon management and (ii)
lexicon-driven applications have been little debated in the past, nor are they
as a part of the present standardization effort. We examine these issues. IGM
has developed XML formats compatible with the emerging international standards,
and we report experimental results on large-coverage lexica.
| 2,005 | Computation and Language |
In memoriam Maurice Gross | Maurice Gross (1934-2001) was both a great linguist and a pioneer in natural
language processing. This article is written in homage to his memory
| 2,005 | Computation and Language |
A resource-based Korean morphological annotation system | We describe a resource-based method of morphological annotation of written
Korean text. Korean is an agglutinative language. The output of our system is a
graph of morphemes annotated with accurate linguistic information. The language
resources used by the system can be easily updated, which allows us-ers to
control the evolution of the per-formances of the system. We show that
morphological annotation of Korean text can be performed directly with a
lexicon of words and without morpho-logical rules.
| 2,005 | Computation and Language |
Graphes param\'etr\'es et outils de lexicalisation | Shifting to a lexicalized grammar reduces the number of parsing errors and
improves application results. However, such an operation affects a syntactic
parser in all its aspects. One of our research objectives is to design a
realistic model for grammar lexicalization. We carried out experiments for
which we used a grammar with a very simple content and formalism, and a very
informative syntactic lexicon, the lexicon-grammar of French elaborated by the
LADL. Lexicalization was performed by applying the parameterized-graph
approach. Our results tend to show that most information in the lexicon-grammar
can be transferred into a grammar and exploited successfully for the syntactic
parsing of sentences.
| 2,006 | Computation and Language |
Evaluation of a Grammar of French Determiners | Existing syntactic grammars of natural languages, even with a far from
complete coverage, are complex objects. Assessments of the quality of parts of
such grammars are useful for the validation of their construction. We evaluated
the quality of a grammar of French determiners that takes the form of a
recursive transition network. The result of the application of this local
grammar gives deeper syntactic information than chunking or information
available in treebanks. We performed the evaluation by comparison with a corpus
independently annotated with information on determiners. We obtained 86%
precision and 92% recall on text not tagged for parts of speech.
| 2,007 | Computation and Language |
Very strict selectional restrictions | We discuss the characteristics and behaviour of two parallel classes of verbs
in two Romance languages, French and Portuguese. Examples of these verbs are
Port. abater [gado] and Fr. abattre [b\'etail], both meaning "slaughter
[cattle]". In both languages, the definition of the class of verbs includes
several features: - They have only one essential complement, which is a direct
object. - The nominal distribution of the complement is very limited, i.e., few
nouns can be selected as head nouns of the complement. However, this selection
is not restricted to a single noun, as would be the case for verbal idioms such
as Fr. monter la garde "mount guard". - We excluded from the class
constructions which are reductions of more complex constructions, e.g. Port.
afinar [instrumento] com "tune [instrument] with".
| 2,006 | Computation and Language |
Outilex, plate-forme logicielle de traitement de textes \'ecrits | The Outilex software platform, which will be made available to research,
development and industry, comprises software components implementing all the
fundamental operations of written text processing: processing without lexicons,
exploitation of lexicons and grammars, language resource management. All data
are structured in XML formats, and also in more compact formats, either
readable or binary, whenever necessary; the required format converters are
included in the platform; the grammar formats allow for combining statistical
approaches with resource-based approaches. Manually constructed lexicons for
French and English, originating from the LADL, and of substantial coverage,
will be distributed with the platform under LGPL-LR license.
| 2,006 | Computation and Language |
Let's get the student into the driver's seat | Speaking a language and achieving proficiency in another one is a highly
complex process which requires the acquisition of various kinds of knowledge
and skills, like the learning of words, rules and patterns and their connection
to communicative goals (intentions), the usual starting point. To help the
learner to acquire these skills we propose an enhanced, electronic version of
an age old method: pattern drills (henceforth PDs). While being highly regarded
in the fifties, PDs have become unpopular since then, partially because of
their lack of grounding (natural context) and rigidity. Despite these
shortcomings we do believe in the virtues of this approach, at least with
regard to the acquisition of basic linguistic reflexes or skills (automatisms),
necessary to survive in the new language. Of course, the method needs
improvement, and we will show here how this can be achieved. Unlike tapes or
books, computers are open media, allowing for dynamic changes, taking users'
performances and preferences into account. Building an electronic version of
PDs amounts to building an open resource, accomodatable to the users' ever
changing needs.
| 2,007 | Computation and Language |
Valence extraction using EM selection and co-occurrence matrices | This paper discusses two new procedures for extracting verb valences from raw
texts, with an application to the Polish language. The first novel technique,
the EM selection algorithm, performs unsupervised disambiguation of valence
frame forests, obtained by applying a non-probabilistic deep grammar parser and
some post-processing to the text. The second new idea concerns filtering of
incorrect frames detected in the parsed text and is motivated by an observation
that verbs which take similar arguments tend to have similar frames. This
phenomenon is described in terms of newly introduced co-occurrence matrices.
Using co-occurrence matrices, we split filtering into two steps. The list of
valid arguments is first determined for each verb, whereas the pattern
according to which the arguments are combined into frames is computed in the
following stage. Our best extracted dictionary reaches an $F$-score of 45%,
compared to an $F$-score of 39% for the standard frame-based BHT filtering.
| 2,009 | Computation and Language |
Framework and Resources for Natural Language Parser Evaluation | Because of the wide variety of contemporary practices used in the automatic
syntactic parsing of natural languages, it has become necessary to analyze and
evaluate the strengths and weaknesses of different approaches. This research is
all the more necessary because there are currently no genre- and
domain-independent parsers that are able to analyze unrestricted text with 100%
preciseness (I use this term to refer to the correctness of analyses assigned
by a parser). All these factors create a need for methods and resources that
can be used to evaluate and compare parsing systems. This research describes:
(1) A theoretical analysis of current achievements in parsing and parser
evaluation. (2) A framework (called FEPa) that can be used to carry out
practical parser evaluations and comparisons. (3) A set of new evaluation
resources: FiEval is a Finnish treebank under construction, and MGTS and RobSet
are parser evaluation resources in English. (4) The results of experiments in
which the developed evaluation framework and the two resources for English were
used for evaluating a set of selected parsers.
| 2,007 | Computation and Language |
The emerging field of language dynamics | A simple review by a linguist, citing many articles by physicists:
Quantitative methods, agent-based computer simulations, language dynamics,
language typology, historical linguistics
| 2,008 | Computation and Language |
A Comparison of natural (english) and artificial (esperanto) languages.
A Multifractal method based analysis | We present a comparison of two english texts, written by Lewis Carroll, one
(Alice in wonderland) and the other (Through a looking glass), the former
translated into esperanto, in order to observe whether natural and artificial
languages significantly differ from each other. We construct one dimensional
time series like signals using either word lengths or word frequencies. We use
the multifractal ideas for sorting out correlations in the writings. In order
to check the robustness of the methods we also write the corresponding shuffled
texts. We compare characteristic functions and e.g. observe marked differences
in the (far from parabolic) f(alpha) curves, differences which we attribute to
Tsallis non extensive statistical features in the ''frequency time series'' and
''length time series''. The esperanto text has more extreme vallues. A very
rough approximation consists in modeling the texts as a random Cantor set if
resulting from a binomial cascade of long and short words (or words and
blanks). This leads to parameters characterizing the text style, and most
likely in fine the author writings.
| 2,008 | Computation and Language |
Online-concordance "Perekhresni stezhky" ("The Cross-Paths"), a novel by
Ivan Franko | In the article, theoretical principles and practical realization for the
compilation of the concordance to "Perekhresni stezhky" ("The Cross-Paths"), a
novel by Ivan Franko, are described. Two forms for the context presentation are
proposed. The electronic version of this lexicographic work is available
online.
| 2,006 | Computation and Language |
Robustness Evaluation of Two CCG, a PCFG and a Link Grammar Parsers | Robustness in a parser refers to an ability to deal with exceptional
phenomena. A parser is robust if it deals with phenomena outside its normal
range of inputs. This paper reports on a series of robustness evaluations of
state-of-the-art parsers in which we concentrated on one aspect of robustness:
its ability to parse sentences containing misspelled words. We propose two
measures for robustness evaluation based on a comparison of a parser's output
for grammatical input sentences and their noisy counterparts. In this paper, we
use these measures to compare the overall robustness of the four evaluated
parsers, and we present an analysis of the decline in parser performance with
increasing error levels. Our results indicate that performance typically
declines tens of percentage units when parsers are presented with texts
containing misspellings. When it was tested on our purpose-built test set of
443 sentences, the best parser in the experiment (C&C parser) was able to
return exactly the same parse tree for the grammatical and ungrammatical
sentences for 60.8%, 34.0% and 14.9% of the sentences with one, two or three
misspelled words respectively.
| 2,007 | Computation and Language |
Between conjecture and memento: shaping a collective emotional
perception of the future | Large scale surveys of public mood are costly and often impractical to
perform. However, the web is awash with material indicative of public mood such
as blogs, emails, and web queries. Inexpensive content analysis on such
extensive corpora can be used to assess public mood fluctuations. The work
presented here is concerned with the analysis of the public mood towards the
future. Using an extension of the Profile of Mood States questionnaire, we have
extracted mood indicators from 10,741 emails submitted in 2006 to futureme.org,
a web service that allows its users to send themselves emails to be delivered
at a later date. Our results indicate long-term optimism toward the future, but
medium-term apprehension and confusion.
| 2,008 | Computation and Language |
Methods to integrate a language model with semantic information for a
word prediction component | Most current word prediction systems make use of n-gram language models (LM)
to estimate the probability of the following word in a phrase. In the past
years there have been many attempts to enrich such language models with further
syntactic or semantic information. We want to explore the predictive powers of
Latent Semantic Analysis (LSA), a method that has been shown to provide
reliable information on long-distance semantic dependencies between words in a
context. We present and evaluate here several methods that integrate LSA-based
information with a standard language model: a semantic cache, partial
reranking, and different forms of interpolation. We found that all methods show
significant improvements, compared to the 4-gram baseline, and most of them to
a simple cache model as well.
| 2,008 | Computation and Language |
Concerning Olga, the Beautiful Little Street Dancer (Adjectives as
Higher-Order Polymorphic Functions) | In this paper we suggest a typed compositional seman-tics for nominal
compounds of the form [Adj Noun] that models adjectives as higher-order
polymorphic functions, and where types are assumed to represent concepts in an
ontology that reflects our commonsense view of the world and the way we talk
about it in or-dinary language. In addition to [Adj Noun] compounds our
proposal seems also to suggest a plausible explana-tion for well known
adjective ordering restrictions.
| 2,008 | Computation and Language |
Textual Fingerprinting with Texts from Parkin, Bassewitz, and Leander | Current research in author profiling to discover a legal author's fingerprint
does not only follow examinations based on statistical parameters only but
include more and more dynamic methods that can learn and that react adaptable
to the specific behavior of an author. But the question on how to appropriately
represent a text is still one of the fundamental tasks, and the problem of
which attribute should be used to fingerprint the author's style is still not
exactly defined. In this work, we focus on linguistic selection of attributes
to fingerprint the style of the authors Parkin, Bassewitz and Leander. We use
texts of the genre Fairy Tale as it has a clear style and texts of a shorter
size with a straightforward story-line and a simple language.
| 2,008 | Computation and Language |
Some properties of the Ukrainian writing system | We investigate the grapheme-phoneme relation in Ukrainian and some properties
of the Ukrainian version of the Cyrillic alphabet.
| 2,008 | Computation and Language |
The Generation of Textual Entailment with NLML in an Intelligent
Dialogue system for Language Learning CSIEC | This research report introduces the generation of textual entailment within
the project CSIEC (Computer Simulation in Educational Communication), an
interactive web-based human-computer dialogue system with natural language for
English instruction. The generation of textual entailment (GTE) is critical to
the further improvement of CSIEC project. Up to now we have found few
literatures related with GTE. Simulating the process that a human being learns
English as a foreign language we explore our naive approach to tackle the GTE
problem and its algorithm within the framework of CSIEC, i.e. rule annotation
in NLML, pattern recognition (matching), and entailment transformation. The
time and space complexity of our algorithm is tested with some entailment
examples. Further works include the rules annotation based on the English
textbooks and a GUI interface for normal users to edit the entailment rules.
| 2,008 | Computation and Language |
Figuring out Actors in Text Streams: Using Collocations to establish
Incremental Mind-maps | The recognition, involvement, and description of main actors influences the
story line of the whole text. This is of higher importance as the text per se
represents a flow of words and expressions that once it is read it is lost. In
this respect, the understanding of a text and moreover on how the actor exactly
behaves is not only a major concern: as human beings try to store a given input
on short-term memory while associating diverse aspects and actors with
incidents, the following approach represents a virtual architecture, where
collocations are concerned and taken as the associative completion of the
actors' acting. Once that collocations are discovered, they become managed in
separated memory blocks broken down by the actors. As for human beings, the
memory blocks refer to associative mind-maps. We then present several priority
functions to represent the actual temporal situation inside a mind-map to
enable the user to reconstruct the recent events from the discovered temporal
results.
| 2,008 | Computation and Language |
Effects of High-Order Co-occurrences on Word Semantic Similarities | A computational model of the construction of word meaning through exposure to
texts is built in order to simulate the effects of co-occurrence values on word
semantic similarities, paragraph by paragraph. Semantic similarity is here
viewed as association. It turns out that the similarity between two words W1
and W2 strongly increases with a co-occurrence, decreases with the occurrence
of W1 without W2 or W2 without W1, and slightly increases with high-order
co-occurrences. Therefore, operationalizing similarity as a frequency of
co-occurrence probably introduces a bias: first, there are cases in which there
is similarity without co-occurrence and, second, the frequency of co-occurrence
overestimates similarity.
| 2,006 | Computation and Language |
Parts-of-Speech Tagger Errors Do Not Necessarily Degrade Accuracy in
Extracting Information from Biomedical Text | A recent study reported development of Muscorian, a generic text processing
tool for extracting protein-protein interactions from text that achieved
comparable performance to biomedical-specific text processing tools. This
result was unexpected since potential errors from a series of text analysis
processes is likely to adversely affect the outcome of the entire process. Most
biomedical entity relationship extraction tools have used biomedical-specific
parts-of-speech (POS) tagger as errors in POS tagging and are likely to affect
subsequent semantic analysis of the text, such as shallow parsing. This study
aims to evaluate the parts-of-speech (POS) tagging accuracy and attempts to
explore whether a comparable performance is obtained when a generic POS tagger,
MontyTagger, was used in place of MedPost, a tagger trained in biomedical text.
Our results demonstrated that MontyTagger, Muscorian's POS tagger, has a POS
tagging accuracy of 83.1% when tested on biomedical text. Replacing MontyTagger
with MedPost did not result in a significant improvement in entity relationship
extraction from text; precision of 55.6% from MontyTagger versus 56.8% from
MedPost on directional relationships and 86.1% from MontyTagger compared to
81.8% from MedPost on nondirectional relationships. This is unexpected as the
potential for poor POS tagging by MontyTagger is likely to affect the outcome
of the information extraction. An analysis of POS tagging errors demonstrated
that 78.5% of tagging errors are being compensated by shallow parsing. Thus,
despite 83.1% tagging accuracy, MontyTagger has a functional tagging accuracy
of 94.6%.
| 2,008 | Computation and Language |
A Semi-Automatic Framework to Discover Epistemic Modalities in
Scientific Articles | Documents in scientific newspapers are often marked by attitudes and opinions
of the author and/or other persons, who contribute with objective and
subjective statements and arguments as well. In this respect, the attitude is
often accomplished by a linguistic modality. As in languages like english,
french and german, the modality is expressed by special verbs like can, must,
may, etc. and the subjunctive mood, an occurrence of modalities often induces
that these verbs take over the role of modality. This is not correct as it is
proven that modality is the instrument of the whole sentence where both the
adverbs, modal particles, punctuation marks, and the intonation of a sentence
contribute. Often, a combination of all these instruments are necessary to
express a modality. In this work, we concern with the finding of modal verbs in
scientific texts as a pre-step towards the discovery of the attitude of an
author. Whereas the input will be an arbitrary text, the output consists of
zones representing modalities.
| 2,008 | Computation and Language |
Phoneme recognition in TIMIT with BLSTM-CTC | We compare the performance of a recurrent neural network with the best
results published so far on phoneme recognition in the TIMIT database. These
published results have been obtained with a combination of classifiers.
However, in this paper we apply a single recurrent neural network to the same
task. Our recurrent neural network attains an error rate of 24.6%. This result
is not significantly different from that obtained by the other best methods,
but they rely on a combination of classifiers for achieving comparable
performance.
| 2,008 | Computation and Language |
Feature Unification in TAG Derivation Trees | The derivation trees of a tree adjoining grammar provide a first insight into
the sentence semantics, and are thus prime targets for generation systems. We
define a formalism, feature-based regular tree grammars, and a translation from
feature based tree adjoining grammars into this new formalism. The translation
preserves the derivation structures of the original grammar, and accounts for
feature unification.
| 2,008 | Computation and Language |
Graph Algorithms for Improving Type-Logical Proof Search | Proof nets are a graph theoretical representation of proofs in various
fragments of type-logical grammar. In spite of this basis in graph theory,
there has been relatively little attention to the use of graph theoretic
algorithms for type-logical proof search. In this paper we will look at several
ways in which standard graph theoretic algorithms can be used to restrict the
search space. In particular, we will provide an O(n4) algorithm for selecting
an optimal axiom link at any stage in the proof search as well as a O(kn3)
algorithm for selecting the k best proof candidates.
| 2,004 | Computation and Language |
A toolkit for a generative lexicon | In this paper we describe the conception of a software toolkit designed for
the construction, maintenance and collaborative use of a Generative Lexicon. In
order to ease its portability and spreading use, this tool was built with free
and open source products. We eventually tested the toolkit and showed it
filters the adequate form of anaphoric reference to the modifier in endocentric
compounds.
| 2,007 | Computation and Language |
Computational Representation of Linguistic Structures using
Domain-Specific Languages | We describe a modular system for generating sentences from formal definitions
of underlying linguistic structures using domain-specific languages. The system
uses Java in general, Prolog for lexical entries and custom domain-specific
languages based on Functional Grammar and Functional Discourse Grammar
notation, implemented using the ANTLR parser generator. We show how linguistic
and technological parts can be brought together in a natural language
processing system and how domain-specific languages can be used as a tool for
consistent formal notation in linguistic description.
| 2,008 | Computation and Language |
Exploring a type-theoretic approach to accessibility constraint
modelling | The type-theoretic modelling of DRT that [degroote06] proposed features
continuations for the management of the context in which a clause has to be
interpreted. This approach, while keeping the standard definitions of
quantifier scope, translates the rules of the accessibility constraints of
discourse referents inside the semantic recipes. In this paper, we deal with
additional rules for these accessibility constraints. In particular in the case
of discourse referents introduced by proper nouns, that negation does not
block, and in the case of rhetorical relations that structure discourses. We
show how this continuation-based approach applies to those accessibility
constraints and how we can consider the parallel management of various
principles.
| 2,008 | Computation and Language |
A semantic space for modeling children's semantic memory | The goal of this paper is to present a model of children's semantic memory,
which is based on a corpus reproducing the kinds of texts children are exposed
to. After presenting the literature in the development of the semantic memory,
a preliminary French corpus of 3.2 million words is described. Similarities in
the resulting semantic space are compared to human data on four tests:
association norms, vocabulary test, semantic judgments and memory tasks. A
second corpus is described, which is composed of subcorpora corresponding to
various ages. This stratified corpus is intended as a basis for developmental
studies. Finally, two applications of these models of semantic memory are
presented: the first one aims at tracing the development of semantic
similarities paragraph by paragraph; the second one describes an implementation
of a model of text comprehension derived from the Construction-integration
model (Kintsch, 1988, 1998) and based on such models of semantic memory.
| 2,007 | Computation and Language |
Textual Entailment Recognizing by Theorem Proving Approach | In this paper we present two original methods for recognizing textual
inference. First one is a modified resolution method such that some linguistic
considerations are introduced in the unification of two atoms. The approach is
possible due to the recent methods of transforming texts in logic formulas.
Second one is based on semantic relations in text, as presented in WordNet.
Some similarities between these two methods are remarked.
| 2,006 | Computation and Language |
A chain dictionary method for Word Sense Disambiguation and applications | A large class of unsupervised algorithms for Word Sense Disambiguation (WSD)
is that of dictionary-based methods. Various algorithms have as the root Lesk's
algorithm, which exploits the sense definitions in the dictionary directly. Our
approach uses the lexical base WordNet for a new algorithm originated in
Lesk's, namely "chain algorithm for disambiguation of all words", CHAD. We show
how translation from a language into another one and also text entailment
verification could be accomplished by this disambiguation.
| 2,007 | Computation and Language |
How Is Meaning Grounded in Dictionary Definitions? | Meaning cannot be based on dictionary definitions all the way down: at some
point the circularity of definitions must be broken in some way, by grounding
the meanings of certain words in sensorimotor categories learned from
experience or shaped by evolution. This is the "symbol grounding problem." We
introduce the concept of a reachable set -- a larger vocabulary whose meanings
can be learned from a smaller vocabulary through definition alone, as long as
the meanings of the smaller vocabulary are themselves already grounded. We
provide simple algorithms to compute reachable sets for any given dictionary.
| 2,008 | Computation and Language |
Computational Approaches to Measuring the Similarity of Short Contexts :
A Review of Applications and Methods | Measuring the similarity of short written contexts is a fundamental problem
in Natural Language Processing. This article provides a unifying framework by
which short context problems can be categorized both by their intended
application and proposed solution. The goal is to show that various problems
and methodologies that appear quite different on the surface are in fact very
closely related. The axes by which these categorizations are made include the
format of the contexts (headed versus headless), the way in which the contexts
are to be measured (first-order versus second-order similarity), and the
information used to represent the features in the contexts (micro versus macro
views). The unifying thread that binds together many short context applications
and methods is the fact that similarity decisions must be made between contexts
that share few (if any) words in common.
| 2,010 | Computation and Language |
About the creation of a parallel bilingual corpora of web-publications | The algorithm of the creation texts parallel corpora was presented. The
algorithm is based on the use of "key words" in text documents, and on the
means of their automated translation. Key words were singled out by means of
using Russian and Ukrainian morphological dictionaries, as well as dictionaries
of the translation of nouns for the Russian and Ukrainianlanguages. Besides, to
calculate the weights of the terms in the documents, empiric-statistic rules
were used. The algorithm under consideration was realized in the form of a
program complex, integrated into the content-monitoring InfoStream system. As a
result, a parallel bilingual corpora of web-publications containing about 30
thousand documents, was created
| 2,008 | Computation and Language |
TuLiPA: Towards a Multi-Formalism Parsing Environment for Grammar
Engineering | In this paper, we present an open-source parsing environment (Tuebingen
Linguistic Parsing Architecture, TuLiPA) which uses Range Concatenation Grammar
(RCG) as a pivot formalism, thus opening the way to the parsing of several
mildly context-sensitive formalisms. This environment currently supports
tree-based grammars (namely Tree-Adjoining Grammars, TAG) and Multi-Component
Tree-Adjoining Grammars with Tree Tuples (TT-MCTAG)) and allows computation not
only of syntactic structures, but also of the corresponding semantic
representations. It is used for the development of a tree-based grammar for
German.
| 2,009 | Computation and Language |
Formal semantics of language and the Richard-Berry paradox | The classical logical antinomy known as Richard-Berry paradox is combined
with plausible assumptions about the size i.e. the descriptional complexity of
Turing machines formalizing certain sentences, to show that formalization of
language leads to contradiction.
| 2,008 | Computation and Language |
Investigation of the Zipf-plot of the extinct Meroitic language | The ancient and extinct language Meroitic is investigated using Zipf's Law.
In particular, since Meroitic is still undeciphered, the Zipf law analysis
allows us to assess the quality of current texts and possible avenues for
future investigation using statistical techniques.
| 2,007 | Computation and Language |
What It Feels Like To Hear Voices: Fond Memories of Julian Jaynes | Julian Jaynes's profound humanitarian convictions not only prevented him from
going to war, but would have prevented him from ever kicking a dog. Yet
according to his theory, not only are language-less dogs unconscious, but so
too were the speaking/hearing Greeks in the Bicameral Era, when they heard
gods' voices telling them what to do rather than thinking for themselves. I
argue that to be conscious is to be able to feel, and that all mammals (and
probably lower vertebrates and invertebrates too) feel, hence are conscious.
Julian Jaynes's brilliant analysis of our concepts of consciousness
nevertheless keeps inspiring ever more inquiry and insights into the age-old
mind/body problem and its relation to cognition and language.
| 2,009 | Computation and Language |
Constructing word similarities in Meroitic as an aid to decipherment | Meroitic is the still undeciphered language of the ancient civilization of
Kush. Over the years, various techniques for decipherment such as finding a
bilingual text or cognates from modern or other ancient languages in the Sudan
and surrounding areas has not been successful. Using techniques borrowed from
information theory and natural language statistics, similar words are paired
and attempts are made to use currently defined words to extract at least
partial meaning from unknown words.
| 2,009 | Computation and Language |
Open architecture for multilingual parallel texts | Multilingual parallel texts (abbreviated to parallel texts) are linguistic
versions of the same content ("translations"); e.g., the Maastricht Treaty in
English and Spanish are parallel texts. This document is about creating an open
architecture for the whole Authoring, Translation and Publishing Chain
(ATP-chain) for the processing of parallel texts.
| 2,008 | Computation and Language |
On the nature of long-range letter correlations in texts | The origin of long-range letter correlations in natural texts is studied
using random walk analysis and Jensen-Shannon divergence. It is concluded that
they result from slow variations in letter frequency distribution, which are a
consequence of slow variations in lexical composition within the text. These
correlations are preserved by random letter shuffling within a moving window.
As such, they do reflect structural properties of the text, but in a very
indirect manner.
| 2,016 | Computation and Language |
A Uniform Approach to Analogies, Synonyms, Antonyms, and Associations | Recognizing analogies, synonyms, antonyms, and associations appear to be four
distinct tasks, requiring distinct NLP algorithms. In the past, the four tasks
have been treated independently, using a wide variety of algorithms. These four
semantic classes, however, are a tiny sample of the full range of semantic
phenomena, and we cannot afford to create ad hoc algorithms for each semantic
phenomenon; we need to seek a unified approach. We propose to subsume a broad
range of phenomena under analogies. To limit the scope of this paper, we
restrict our attention to the subsumption of synonyms, antonyms, and
associations. We introduce a supervised corpus-based machine learning algorithm
for classifying analogous word pairs, and we show that it can solve
multiple-choice SAT analogy questions, TOEFL synonym questions, ESL
synonym-antonym questions, and similar-associated-both questions from cognitive
psychology.
| 2,008 | Computation and Language |
Using descriptive mark-up to formalize translation quality assessment | The paper deals with using descriptive mark-up to emphasize translation
mistakes. The author postulates the necessity to develop a standard and formal
XML-based way of describing translation mistakes. It is considered to be
important for achieving impersonal translation quality assessment. Marked-up
translations can be used in corpus translation studies; moreover, automatic
translation assessment based on marked-up mistakes is possible. The paper
concludes with setting up guidelines for further activity within the described
field.
| 2,008 | Computation and Language |
Distribution of complexities in the Vai script | In the paper, we analyze the distribution of complexities in the Vai script,
an indigenous syllabic writing system from Liberia. It is found that the
uniformity hypothesis for complexities fails for this script. The models using
Poisson distribution for the number of components and hyper-Poisson
distribution for connections provide good fits in the case of the Vai script.
| 2,009 | Computation and Language |
Une grammaire formelle du cr\'eole martiniquais pour la g\'en\'eration
automatique | In this article, some first elements of a computational modelling of the
grammar of the Martiniquese French Creole dialect are presented. The sources of
inspiration for the modelling is the functional description given by Damoiseau
(1984), and Pinalie's & Bernabe's (1999) grammar manual. Based on earlier works
in text generation (Vaillant, 1997), a unification grammar formalism, namely
Tree Adjoining Grammars (TAG), and a modelling of lexical functional categories
based on syntactic and semantic properties, are used to implement a grammar of
Martiniquese Creole which is used in a prototype of text generation system. One
of the main applications of the system could be its use as a tool software
supporting the task of learning Creole as a second language. -- Nous
pr\'esenterons dans cette communication les premiers travaux de mod\'elisation
informatique d'une grammaire de la langue cr\'eole martiniquaise, en nous
inspirant des descriptions fonctionnelles de Damoiseau (1984) ainsi que du
manuel de Pinalie & Bernab\'e (1999). Prenant appui sur des travaux
ant\'erieurs en g\'en\'eration de texte (Vaillant, 1997), nous utilisons un
formalisme de grammaires d'unification, les grammaires d'adjonction d'arbres
(TAG d'apr\`es l'acronyme anglais), ainsi qu'une mod\'elisation de cat\'egories
lexicales fonctionnelles \`a base syntaxico-s\'emantique, pour mettre en oeuvre
une grammaire du cr\'eole martiniquais utilisable dans une maquette de
syst\`eme de g\'en\'eration automatique. L'un des int\'er\^ets principaux de ce
syst\`eme pourrait \^etre son utilisation comme logiciel outil pour l'aide \`a
l'apprentissage du cr\'eole en tant que langue seconde.
| 2,003 | Computation and Language |
A Layered Grammar Model: Using Tree-Adjoining Grammars to Build a Common
Syntactic Kernel for Related Dialects | This article describes the design of a common syntactic description for the
core grammar of a group of related dialects. The common description does not
rely on an abstract sub-linguistic structure like a metagrammar: it consists in
a single FS-LTAG where the actual specific language is included as one of the
attributes in the set of attribute types defined for the features. When the
lang attribute is instantiated, the selected subset of the grammar is
equivalent to the grammar of one dialect. When it is not, we have a model of a
hybrid multidialectal linguistic system. This principle is used for a group of
creole languages of the West-Atlantic area, namely the French-based Creoles of
Haiti, Guadeloupe, Martinique and French Guiana.
| 2,008 | Computation and Language |
Analyse spectrale des textes: d\'etection automatique des fronti\`eres
de langue et de discours | We propose a theoretical framework within which information on the vocabulary
of a given corpus can be inferred on the basis of statistical information
gathered on that corpus. Inferences can be made on the categories of the words
in the vocabulary, and on their syntactical properties within particular
languages. Based on the same statistical data, it is possible to build matrices
of syntagmatic similarity (bigram transition matrices) or paradigmatic
similarity (probability for any pair of words to share common contexts). When
clustered with respect to their syntagmatic similarity, words tend to group
into sublanguage vocabularies, and when clustered with respect to their
paradigmatic similarity, into syntactic or semantic classes. Experiments have
explored the first of these two possibilities. Their results are interpreted in
the frame of a Markov chain modelling of the corpus' generative processe(s): we
show that the results of a spectral analysis of the transition matrix can be
interpreted as probability distributions of words within clusters. This method
yields a soft clustering of the vocabulary into sublanguages which contribute
to the generation of heterogeneous corpora. As an application, we show how
multilingual texts can be visually segmented into linguistically homogeneous
segments. Our method is specifically useful in the case of related languages
which happened to be mixed in corpora.
| 2,006 | Computation and Language |
Soft Uncoupling of Markov Chains for Permeable Language Distinction: A
New Algorithm | Without prior knowledge, distinguishing different languages may be a hard
task, especially when their borders are permeable. We develop an extension of
spectral clustering -- a powerful unsupervised classification toolbox -- that
is shown to resolve accurately the task of soft language distinction. At the
heart of our approach, we replace the usual hard membership assignment of
spectral clustering by a soft, probabilistic assignment, which also presents
the advantage to bypass a well-known complexity bottleneck of the method.
Furthermore, our approach relies on a novel, convenient construction of a
Markov chain out of a corpus. Extensive experiments with a readily available
system clearly display the potential of the method, which brings a visually
appealing soft distinction of languages that may define altogether a whole
corpus.
| 2,006 | Computation and Language |
Text as Statistical Mechanics Object | In this article we present a model of human written text based on statistical
mechanics approach by deriving the potential energy for different parts of the
text using large text corpus. We have checked the results numerically and found
that the specific heat parameter effectively separates the closed class words
from the specific terms used in the text.
| 2,008 | Computation and Language |
Language structure in the n-object naming game | We examine a naming game with two agents trying to establish a common
vocabulary for n objects. Such efforts lead to the emergence of language that
allows for an efficient communication and exhibits some degree of homonymy and
synonymy. Although homonymy reduces the communication efficiency, it seems to
be a dynamical trap that persists for a long, and perhaps indefinite, time. On
the other hand, synonymy does not reduce the efficiency of communication, but
appears to be only a transient feature of the language. Thus, in our model the
role of synonymy decreases and in the long-time limit it becomes negligible. A
similar rareness of synonymy is observed in present natural languages. The role
of noise, that distorts the communicated words, is also examined. Although, in
general, the noise reduces the communication efficiency, it also regroups the
words so that they are more evenly distributed within the available "verbal"
space.
| 2,009 | Computation and Language |
Assembling Actor-based Mind-Maps from Text Stream | For human beings, the processing of text streams of unknown size leads
generally to problems because e.g. noise must be selected out, information be
tested for its relevance or redundancy, and linguistic phenomenon like
ambiguity or the resolution of pronouns be advanced. Putting this into
simulation by using an artificial mind-map is a challenge, which offers the
gate for a wide field of applications like automatic text summarization or
punctual retrieval. In this work we present a framework that is a first step
towards an automatic intellect. It aims at assembling a mind-map based on
incoming text streams and on a subject-verb-object strategy, having the verb as
an interconnection between the adjacent nouns. The mind-map's performance is
enriched by a pronoun resolution engine that bases on the work of D. Klein, and
C. D. Manning.
| 2,008 | Computation and Language |
CoZo+ - A Content Zoning Engine for textual documents | Content zoning can be understood as a segmentation of textual documents into
zones. This is inspired by [6] who initially proposed an approach for the
argumentative zoning of textual documents. With the prototypical CoZo+ engine,
we focus on content zoning towards an automatic processing of textual streams
while considering only the actors as the zones. We gain information that can be
used to realize an automatic recognition of content for pre-defined actors. We
understand CoZo+ as a necessary pre-step towards an automatic generation of
summaries and to make intellectual ownership of documents detectable.
| 2,008 | Computation and Language |
UNL-French deconversion as transfer & generation from an interlingua
with possible quality enhancement through offline human interaction | We present the architecture of the UNL-French deconverter, which "generates"
from the UNL interlingua by first"localizing" the UNL form for French, within
UNL, and then applying slightly adapted but classical transfer and generation
techniques, implemented in GETA's Ariane-G5 environment, supplemented by some
UNL-specific tools. Online interaction can be used during deconversion to
enhance output quality and is now used for development purposes. We show how
interaction could be delayed and embedded in the postedition phase, which would
then interact not directly with the output text, but indirectly with several
components of the deconverter. Interacting online or offline can improve the
quality not only of the utterance at hand, but also of the utterances processed
later, as various preferences may be automatically changed to let the
deconverter "learn".
| 1,999 | Computation and Language |
The Application of Fuzzy Logic to Collocation Extraction | Collocations are important for many tasks of Natural language processing such
as information retrieval, machine translation, computational lexicography etc.
So far many statistical methods have been used for collocation extraction.
Almost all the methods form a classical crisp set of collocation. We propose a
fuzzy logic approach of collocation extraction to form a fuzzy set of
collocations in which each word combination has a certain grade of membership
for being collocation. Fuzzy logic provides an easy way to express natural
language into fuzzy logic rules. Two existing methods; Mutual information and
t-test have been utilized for the input of the fuzzy inference system. The
resulting membership function could be easily seen and demonstrated. To show
the utility of the fuzzy logic some word pairs have been examined as an
example. The working data has been based on a corpus of about one million words
contained in different novels constituting project Gutenberg available on
www.gutenberg.org. The proposed method has all the advantages of the two
methods, while overcoming their drawbacks. Hence it provides a better result
than the two methods.
| 2,008 | Computation and Language |
A Computational Model to Disentangle Semantic Information Embedded in
Word Association Norms | Two well-known databases of semantic relationships between pairs of words
used in psycholinguistics, feature-based and association-based, are studied as
complex networks. We propose an algorithm to disentangle feature based
relationships from free association semantic networks. The algorithm uses the
rich topology of the free association semantic network to produce a new set of
relationships between words similar to those observed in feature production
norms.
| 2,008 | Computation and Language |
The Latent Relation Mapping Engine: Algorithm and Experiments | Many AI researchers and cognitive scientists have argued that analogy is the
core of cognition. The most influential work on computational modeling of
analogy-making is Structure Mapping Theory (SMT) and its implementation in the
Structure Mapping Engine (SME). A limitation of SME is the requirement for
complex hand-coded representations. We introduce the Latent Relation Mapping
Engine (LRME), which combines ideas from SME and Latent Relational Analysis
(LRA) in order to remove the requirement for hand-coded representations. LRME
builds analogical mappings between lists of words, using a large corpus of raw
text to automatically discover the semantic relations among the words. We
evaluate LRME on a set of twenty analogical mapping problems, ten based on
scientific analogies and ten based on common metaphors. LRME achieves
human-level performance on the twenty problems. We compare LRME with a variety
of alternative approaches and find that they are not able to reach the same
level of performance.
| 2,008 | Computation and Language |
Discovering Global Patterns in Linguistic Networks through Spectral
Analysis: A Case Study of the Consonant Inventories | Recent research has shown that language and the socio-cognitive phenomena
associated with it can be aptly modeled and visualized through networks of
linguistic entities. However, most of the existing works on linguistic networks
focus only on the local properties of the networks. This study is an attempt to
analyze the structure of languages via a purely structural technique, namely
spectral analysis, which is ideally suited for discovering the global
correlations in a network. Application of this technique to PhoNet, the
co-occurrence network of consonants, not only reveals several natural
linguistic principles governing the structure of the consonant inventories, but
is also able to quantify their relative importance. We believe that this
powerful technique can be successfully applied, in general, to study the
structure of natural languages.
| 2,009 | Computation and Language |
Beyond word frequency: Bursts, lulls, and scaling in the temporal
distributions of words | Background: Zipf's discovery that word frequency distributions obey a power
law established parallels between biological and physical processes, and
language, laying the groundwork for a complex systems perspective on human
communication. More recent research has also identified scaling regularities in
the dynamics underlying the successive occurrences of events, suggesting the
possibility of similar findings for language as well.
Methodology/Principal Findings: By considering frequent words in USENET
discussion groups and in disparate databases where the language has different
levels of formality, here we show that the distributions of distances between
successive occurrences of the same word display bursty deviations from a
Poisson process and are well characterized by a stretched exponential (Weibull)
scaling. The extent of this deviation depends strongly on semantic type -- a
measure of the logicality of each word -- and less strongly on frequency. We
develop a generative model of this behavior that fully determines the dynamics
of word usage.
Conclusions/Significance: Recurrence patterns of words are well described by
a stretched exponential distribution of recurrence times, an empirical scaling
that cannot be anticipated from Zipf's law. Because the use of words provides a
uniquely precise and powerful lens on human thought and activity, our findings
also have implications for other overt manifestations of collective human
dynamics.
| 2,009 | Computation and Language |
Statistical analysis of the Indus script using $n$-grams | The Indus script is one of the major undeciphered scripts of the ancient
world. The small size of the corpus, the absence of bilingual texts, and the
lack of definite knowledge of the underlying language has frustrated efforts at
decipherment since the discovery of the remains of the Indus civilisation.
Recently, some researchers have questioned the premise that the Indus script
encodes spoken language. Building on previous statistical approaches, we apply
the tools of statistical language processing, specifically $n$-gram Markov
chains, to analyse the Indus script for syntax. Our main results are that the
script has well-defined signs which begin and end texts, that there is
directionality and strong correlations in the sign order, and that there are
groups of signs which appear to have identical syntactic function. All these
require no {\it a priori} suppositions regarding the syntactic or semantic
content of the signs, but follow directly from the statistical analysis. Using
information theoretic measures, we find the information in the script to be
intermediate between that of a completely random and a completely fixed
ordering of signs. Our study reveals that the Indus script is a structured sign
system showing features of a formal language, but, at present, cannot
conclusively establish that it encodes {\it natural} language. Our $n$-gram
Markov model is useful for predicting signs which are missing or illegible in a
corpus of Indus texts. This work forms the basis for the development of a
stochastic grammar which can be used to explore the syntax of the Indus script
in greater detail.
| 2,015 | Computation and Language |
Approaching the linguistic complexity | We analyze the rank-frequency distributions of words in selected English and
Polish texts. We compare scaling properties of these distributions in both
languages. We also study a few small corpora of Polish literary texts and find
that for a corpus consisting of texts written by different authors the basic
scaling regime is broken more strongly than in the case of comparable corpus
consisting of texts written by the same author. Similarly, for a corpus
consisting of texts translated into Polish from other languages the scaling
regime is broken more strongly than for a comparable corpus of native Polish
texts. Moreover, based on the British National Corpus, we consider the
rank-frequency distributions of the grammatically basic forms of words (lemmas)
tagged with their proper part of speech. We find that these distributions do
not scale if each part of speech is analyzed separately. The only part of
speech that independently develops a trace of scaling is verbs.
| 2,009 | Computation and Language |
Du corpus au dictionnaire | In this article, we propose an automatic process to build multi-lingual
lexico-semantic resources. The goal of these resources is to browse
semantically textual information contained in texts of different languages.
This method uses a mathematical model called Atlas s\'emantiques in order to
represent the different senses of each word. It uses the linguistic relations
between words to create graphs that are projected into a semantic space. These
projections constitute semantic maps that denote the sense trends of each given
word. This model is fed with syntactic relations between words extracted from a
corpus. Therefore, the lexico-semantic resource produced describes all the
words and all their meanings observed in the corpus. The sense trends are
expressed by syntactic contexts, typical for a given meaning. The link between
each sense trend and the utterances used to build the sense trend are also
stored in an index. Thus all the instances of a word in a particular sense are
linked and can be browsed easily. And by using several corpora of different
languages, several resources are built that correspond with each other through
languages. It makes it possible to browse information through languages thanks
to syntactic contexts translations (even if some of them are partial).
| 2,008 | Computation and Language |
Google distance between words | Cilibrasi and Vitanyi have demonstrated that it is possible to extract the
meaning of words from the world-wide web. To achieve this, they rely on the
number of webpages that are found through a Google search containing a given
word and they associate the page count to the probability that the word appears
on a webpage. Thus, conditional probabilities allow them to correlate one word
with another word's meaning. Furthermore, they have developed a similarity
distance function that gauges how closely related a pair of words is. We
present a specific counterexample to the triangle inequality for this
similarity distance function.
| 2,015 | Computation and Language |
On the Entropy of Written Spanish | This paper reports on results on the entropy of the Spanish language. They
are based on an analysis of natural language for n-word symbols (n = 1 to 18),
trigrams, digrams, and characters. The results obtained in this work are based
on the analysis of twelve different literary works in Spanish, as well as a
279917 word news file provided by the Spanish press agency EFE. Entropy values
are calculated by a direct method using computer processing and the probability
law of large numbers. Three samples of artificial Spanish language produced by
a first-order model software source are also analyzed and compared with natural
Spanish language.
| 2,012 | Computation and Language |
Beyond Zipf's law: Modeling the structure of human language | Human language, the most powerful communication system in history, is closely
associated with cognition. Written text is one of the fundamental
manifestations of language, and the study of its universal regularities can
give clues about how our brains process information and how we, as a society,
organize and share it. Still, only classical patterns such as Zipf's law have
been explored in depth. In contrast, other basic properties like the existence
of bursts of rare words in specific documents, the topical organization of
collections, or the sublinear growth of vocabulary size with the length of a
document, have only been studied one by one and mainly applying heuristic
methodologies rather than basic principles and general mechanisms. As a
consequence, there is a lack of understanding of linguistic processes as
complex emergent phenomena. Beyond Zipf's law for word frequencies, here we
focus on Heaps' law, burstiness, and the topicality of document collections,
which encode correlations within and across documents absent in random null
models. We introduce and validate a generative model that explains the
simultaneous emergence of all these patterns from simple rules. As a result, we
find a connection between the bursty nature of rare words and the topical
organization of texts and identify dynamic word ranking and memory across
documents as key mechanisms explaining the non trivial organization of written
text. Our research can have broad implications and practical applications in
computer science, cognitive science, and linguistics.
| 2,009 | Computation and Language |
New Confidence Measures for Statistical Machine Translation | A confidence measure is able to estimate the reliability of an hypothesis
provided by a machine translation system. The problem of confidence measure can
be seen as a process of testing : we want to decide whether the most probable
sequence of words provided by the machine translation system is correct or not.
In the following we describe several original word-level confidence measures
for machine translation, based on mutual information, n-gram language model and
lexical features language model. We evaluate how well they perform individually
or together, and show that using a combination of confidence measures based on
mutual information yields a classification error rate as low as 25.1% with an
F-measure of 0.708.
| 2,009 | Computation and Language |
BagPack: A general framework to represent semantic relations | We introduce a way to represent word pairs instantiating arbitrary semantic
relations that keeps track of the contexts in which the words in the pair occur
both together and independently. The resulting features are of sufficient
generality to allow us, with the help of a standard supervised machine learning
algorithm, to tackle a variety of unrelated semantic tasks with good results
and almost no task-specific tailoring.
| 2,009 | Computation and Language |
What's in a Message? | In this paper we present the first step in a larger series of experiments for
the induction of predicate/argument structures. The structures that we are
inducing are very similar to the conceptual structures that are used in Frame
Semantics (such as FrameNet). Those structures are called messages and they
were previously used in the context of a multi-document summarization system of
evolving events. The series of experiments that we are proposing are
essentially composed from two stages. In the first stage we are trying to
extract a representative vocabulary of words. This vocabulary is later used in
the second stage, during which we apply to it various clustering approaches in
order to identify the clusters of predicates and arguments--or frames and
semantic roles, to use the jargon of Frame Semantics. This paper presents in
detail and evaluates the first stage.
| 2,009 | Computation and Language |
Syntactic variation of support verb constructions | We report experiments about the syntactic variations of support verb
constructions, a special type of multiword expressions (MWEs) containing
predicative nouns. In these expressions, the noun can occur with or without the
verb, with no clear-cut semantic difference. We extracted from a large French
corpus a set of examples of the two situations and derived statistical results
from these data. The extraction involved large-coverage language resources and
finite-state techniques. The results show that, most frequently, predicative
nouns occur without a support verb. This fact has consequences on methods of
extracting or recognising MWEs.
| 2,008 | Computation and Language |
Network of two-Chinese-character compound words in Japanese language | Some statistical properties of a network of two-Chinese-character compound
words in Japanese language are reported. In this network, a node represents a
Chinese character and an edge represents a two-Chinese-character compound word.
It is found that this network has properties of "small-world" and "scale-free."
A network formed by only Chinese characters for common use ({\it joyo-kanji} in
Japanese), which is regarded as a subclass of the original network, also has
small-world property. However, a degree distribution of the network exhibits no
clear power law. In order to reproduce disappearance of the power-law property,
a model for a selecting process of the Chinese characters for common use is
proposed.
| 2,009 | Computation and Language |
End of preview. Expand
in Dataset Viewer.
arXiv Abstracts
Abstracts for the cs.CL category of ArXiv between 1991 and 2024. This dataset was created as an instructional tool for the Clustering and Topic Modeling chapter in the upcoming
"Hands-On Large Language Models" book.
The original dataset was retrieved here.
This subset will be updated towards the release of the book to make sure it captures relatively recent articles in the domain.
- Downloads last month
- 574