Titles
string | Abstracts
string | Years
int64 | Categories
string |
|---|---|---|---|
Mathematical Model for Transformation of Sentences from Active Voice to
Passive Voice | Formal work in linguistics has both produced and used important mathematical
tools. Motivated by a survey of models for context and word meaning, syntactic
categories, phrase structure rules and trees, an attempt is being made in the
present paper to present a mathematical model for structuring of sentences from
active voice to passive voice, which is is the form of a transitive verb whose
grammatical subject serves as the patient, receiving the action of the verb.
For this purpose we have parsed all sentences of a corpus and have generated
Boolean groups for each of them. It has been observed that when we take
constituents of the sentences as subgroups, the sequences of phrases form
permutation roups. Application of isomorphism property yields permutation
mapping between the important subgroups. It has resulted in a model for
transformation of sentences from active voice to passive voice. A computer
program has been written to enable the software developers to evolve grammar
software for sentence transformations.
| 2,009 | Computation and Language |
Language Diversity across the Consonant Inventories: A Study in the
Framework of Complex Networks | n this paper, we attempt to explain the emergence of the linguistic diversity
that exists across the consonant inventories of some of the major language
families of the world through a complex network based growth model. There is
only a single parameter for this model that is meant to introduce a small
amount of randomness in the otherwise preferential attachment based growth
process. The experiments with this model parameter indicates that the choice of
consonants among the languages within a family are far more preferential than
it is across the families. The implications of this result are twofold -- (a)
there is an innate preference of the speakers towards acquiring certain
linguistic structures over others and (b) shared ancestry propels the stronger
preferential connection between the languages within a family than across them.
Furthermore, our observations indicate that this parameter might bear a
correlation with the period of existence of the language families under
investigation.
| 2,009 | Computation and Language |
Acquisition of morphological families and derivational series from a
machine readable dictionary | The paper presents a linguistic and computational model aiming at making the
morphological structure of the lexicon emerge from the formal and semantic
regularities of the words it contains. The model is word-based. The proposed
morphological structure consists of (1) binary relations that connect each
headword with words that are morphologically related, and especially with the
members of its morphological family and its derivational series, and of (2) the
analogies that hold between the words. The model has been tested on the lexicon
of French using the TLFi machine readable dictionary.
| 2,009 | Computation and Language |
An Object-Oriented and Fast Lexicon for Semantic Generation | This paper is about the technical design of a large computational lexicon,
its storage, and its access from a Prolog environment. Traditionally, efficient
access and storage of data structures is implemented by a relational database
management system. In Delilah, a lexicon-based NLP system, efficient access to
the lexicon by the semantic generator is vital. We show that our highly
detailed HPSG-style lexical specifications do not fit well in the Relational
Model, and that they cannot be efficiently retrieved. We argue that they fit
more naturally in the Object-Oriented Model. Although storage of objects is
redundant, we claim that efficient access is still possible by applying
indexing, and compression techniques from the Relational Model to the
Object-Oriented Model. We demonstrate that it is possible to implement
object-oriented storage and fast access in ISO Prolog.
| 2,009 | Computation and Language |
Normalized Web Distance and Word Similarity | There is a great deal of work in cognitive psychology, linguistics, and
computer science, about using word (or phrase) frequencies in context in text
corpora to develop measures for word similarity or word association, going back
to at least the 1960s. The goal of this chapter is to introduce the
normalizedis a general way to tap the amorphous low-grade knowledge available
for free on the Internet, typed in by local users aiming at personal
gratification of diverse objectives, and yet globally achieving what is
effectively the largest semantic electronic database in the world. Moreover,
this database is available for all by using any search engine that can return
aggregate page-count estimates for a large range of search-queries. In the
paper introducing the NWD it was called `normalized Google distance (NGD),' but
since Google doesn't allow computer searches anymore, we opt for the more
neutral and descriptive NWD. web distance (NWD) method to determine similarity
between words and phrases. It
| 2,009 | Computation and Language |
Encoding models for scholarly literature | We examine the issue of digital formats for document encoding, archiving and
publishing, through the specific example of "born-digital" scholarly journal
articles. We will begin by looking at the traditional workflow of journal
editing and publication, and how these practices have made the transition into
the online domain. We will examine the range of different file formats in which
electronic articles are currently stored and published. We will argue strongly
that, despite the prevalence of binary and proprietary formats such as PDF and
MS Word, XML is a far superior encoding choice for journal articles. Next, we
look at the range of XML document structures (DTDs, Schemas) which are in
common use for encoding journal articles, and consider some of their strengths
and weaknesses. We will suggest that, despite the existence of specialized
schemas intended specifically for journal articles (such as NLM), and more
broadly-used publication-oriented schemas such as DocBook, there are strong
arguments in favour of developing a subset or customization of the Text
Encoding Initiative (TEI) schema for the purpose of journal-article encoding;
TEI is already in use in a number of journal publication projects, and the
scale and precision of the TEI tagset makes it particularly appropriate for
encoding scholarly articles. We will outline the document structure of a
TEI-encoded journal article, and look in detail at suggested markup patterns
for specific features of journal articles.
| 2,010 | Computation and Language |
Size dependent word frequencies and translational invariance of books | It is shown that a real novel shares many characteristic features with a null
model in which the words are randomly distributed throughout the text. Such a
common feature is a certain translational invariance of the text. Another is
that the functional form of the word-frequency distribution of a novel depends
on the length of the text in the same way as the null model. This means that an
approximate power-law tail ascribed to the data will have an exponent which
changes with the size of the text-section which is analyzed. A further
consequence is that a novel cannot be described by text-evolution models like
the Simon model. The size-transformation of a novel is found to be well
described by a specific Random Book Transformation. This size transformation in
addition enables a more precise determination of the functional form of the
word-frequency distribution. The implications of the results are discussed.
| 2,010 | Computation and Language |
Properties of quasi-alphabetic tree bimorphisms | We study the class of quasi-alphabetic relations, i.e., tree transformations
defined by tree bimorphisms with two quasi-alphabetic tree homomorphisms and a
regular tree language. We present a canonical representation of these
relations; as an immediate consequence, we get the closure under union. Also,
we show that they are not closed under intersection and complement, and do not
preserve most common operations on trees (branches, subtrees, v-product,
v-quotient, f-top-catenation). Moreover, we prove that the translations defined
by quasi-alphabetic tree bimorphism are exactly products of context-free string
languages. We conclude by presenting the connections between quasi-alphabetic
relations, alphabetic relations and classes of tree transformations defined by
several types of top-down tree transducers. Furthermore, we get that
quasi-alphabetic relations preserve the recognizable and algebraic tree
languages.
| 2,010 | Computation and Language |
Without a 'doubt'? Unsupervised discovery of downward-entailing
operators | An important part of textual inference is making deductions involving
monotonicity, that is, determining whether a given assertion entails
restrictions or relaxations of that assertion. For instance, the statement 'We
know the epidemic spread quickly' does not entail 'We know the epidemic spread
quickly via fleas', but 'We doubt the epidemic spread quickly' entails 'We
doubt the epidemic spread quickly via fleas'. Here, we present the first
algorithm for the challenging lexical-semantics problem of learning linguistic
constructions that, like 'doubt', are downward entailing (DE). Our algorithm is
unsupervised, resource-lean, and effective, accurately recovering many DE
operators that are missing from the hand-constructed lists that
textual-inference systems currently use.
| 2,009 | Computation and Language |
How opinions are received by online communities: A case study on
Amazon.com helpfulness votes | There are many on-line settings in which users publicly express opinions. A
number of these offer mechanisms for other users to evaluate these opinions; a
canonical example is Amazon.com, where reviews come with annotations like "26
of 32 people found the following review helpful." Opinion evaluation appears in
many off-line settings as well, including market research and political
campaigns. Reasoning about the evaluation of an opinion is fundamentally
different from reasoning about the opinion itself: rather than asking, "What
did Y think of X?", we are asking, "What did Z think of Y's opinion of X?" Here
we develop a framework for analyzing and modeling opinion evaluation, using a
large-scale collection of Amazon book reviews as a dataset. We find that the
perceived helpfulness of a review depends not just on its content but also but
also in subtle ways on how the expressed evaluation relates to other
evaluations of the same product. As part of our approach, we develop novel
methods that take advantage of the phenomenon of review "plagiarism" to control
for the effects of text in opinion evaluation, and we provide a simple and
natural mathematical model consistent with our findings. Our analysis also
allows us to distinguish among the predictions of competing theories from
sociology and social psychology, and to discover unexpected differences in the
collective opinion-evaluation behavior of user populations from different
countries.
| 2,009 | Computation and Language |
Non-Parametric Bayesian Areal Linguistics | We describe a statistical model over linguistic areas and phylogeny.
Our model recovers known areas and identifies a plausible hierarchy of areal
features. The use of areas improves genetic reconstruction of languages both
qualitatively and quantitatively according to a variety of metrics. We model
linguistic areas by a Pitman-Yor process and linguistic phylogeny by Kingman's
coalescent.
| 2,009 | Computation and Language |
A Bayesian Model for Discovering Typological Implications | A standard form of analysis for linguistic typology is the universal
implication. These implications state facts about the range of extant
languages, such as ``if objects come after verbs, then adjectives come after
nouns.'' Such implications are typically discovered by painstaking hand
analysis over a small sample of languages. We propose a computational model for
assisting at this process. Our model is able to discover both well-known
implications as well as some novel implications that deserve further study.
Moreover, through a careful application of hierarchical analysis, we are able
to cope with the well-known sampling problem: languages are not independent.
| 2,007 | Computation and Language |
Induction of Word and Phrase Alignments for Automatic Document
Summarization | Current research in automatic single document summarization is dominated by
two effective, yet naive approaches: summarization by sentence extraction, and
headline generation via bag-of-words models. While successful in some tasks,
neither of these models is able to adequately capture the large set of
linguistic devices utilized by humans when they produce summaries. One possible
explanation for the widespread use of these models is that good techniques have
been developed to extract appropriate training data for them from existing
document/abstract and document/headline corpora. We believe that future
progress in automatic summarization will be driven both by the development of
more sophisticated, linguistically informed models, as well as a more effective
leveraging of document/abstract corpora. In order to open the doors to
simultaneously achieving both of these goals, we have developed techniques for
automatically producing word-to-word and phrase-to-phrase alignments between
documents and their human-written abstracts. These alignments make explicit the
correspondences that exist in such document/abstract pairs, and create a
potentially rich data source from which complex summarization algorithms may
learn. This paper describes experiments we have carried out to analyze the
ability of humans to perform such alignments, and based on these analyses, we
describe experiments for creating them automatically. Our model for the
alignment task is based on an extension of the standard hidden Markov model,
and learns to create alignments in a completely unsupervised fashion. We
describe our model in detail and present experimental results that show that
our model is able to learn to reliably identify word- and phrase-level
alignments in a corpus of <document,abstract> pairs.
| 2,005 | Computation and Language |
A Noisy-Channel Model for Document Compression | We present a document compression system that uses a hierarchical
noisy-channel model of text production. Our compression system first
automatically derives the syntactic structure of each sentence and the overall
discourse structure of the text given as input. The system then uses a
statistical hierarchical model of text production in order to drop
non-important syntactic and discourse constituents so as to generate coherent,
grammatical document compressions of arbitrary length. The system outperforms
both a baseline and a sentence-based compression system that operates by
simplifying sequentially all sentences in a text. Our results support the claim
that discourse knowledge plays an important role in document summarization.
| 2,002 | Computation and Language |
A Large-Scale Exploration of Effective Global Features for a Joint
Entity Detection and Tracking Model | Entity detection and tracking (EDT) is the task of identifying textual
mentions of real-world entities in documents, extending the named entity
detection and coreference resolution task by considering mentions other than
names (pronouns, definite descriptions, etc.). Like NE tagging and coreference
resolution, most solutions to the EDT task separate out the mention detection
aspect from the coreference aspect. By doing so, these solutions are limited to
using only local features for learning. In contrast, by modeling both aspects
of the EDT task simultaneously, we are able to learn using highly complex,
non-local features. We develop a new joint EDT model and explore the utility of
many features, demonstrating their effectiveness on this task.
| 2,005 | Computation and Language |
Bayesian Query-Focused Summarization | We present BayeSum (for ``Bayesian summarization''), a model for sentence
extraction in query-focused summarization. BayeSum leverages the common case in
which multiple documents are relevant to a single query. Using these documents
as reinforcement for query terms, BayeSum is not afflicted by the paucity of
information in short queries. We show that approximate inference in BayeSum is
possible on large data sets and results in a state-of-the-art summarization
system. Furthermore, we show how BayeSum can be understood as a justified query
expansion technique in the language modeling for IR framework.
| 2,006 | Computation and Language |
Pattern Based Term Extraction Using ACABIT System | In this paper, we propose a pattern-based term extraction approach for
Japanese, applying ACABIT system originally developed for French. The proposed
approach evaluates termhood using morphological patterns of basic terms and
term variants. After extracting term candidates, ACABIT system filters out
non-terms from the candidates based on log-likelihood. This approach is
suitable for Japanese term extraction because most of Japanese terms are
compound nouns or simple phrasal patterns.
| 2,003 | Computation and Language |
Un syst\`eme modulaire d'acquisition automatique de traductions \`a
partir du Web | We present a method of automatic translation (French/English) of Complex
Lexical Units (CLU) for aiming at extracting a bilingual lexicon. Our modular
system is based on linguistic properties (compositionality, polysemy, etc.).
Different aspects of the multilingual Web are used to validate candidate
translations and collect new terms. We first build a French corpus of Web pages
to collect CLU. Three adapted processing stages are applied for each linguistic
property : compositional and non polysemous translations, compositional
polysemous translations and non compositional translations. Our evaluation on a
sample of CLU shows that our technique based on the Web can reach a very high
precision.
| 2,009 | Computation and Language |
Multiple Retrieval Models and Regression Models for Prior Art Search | This paper presents the system called PATATRAS (PATent and Article Tracking,
Retrieval and AnalysiS) realized for the IP track of CLEF 2009. Our approach
presents three main characteristics: 1. The usage of multiple retrieval models
(KL, Okapi) and term index definitions (lemma, phrase, concept) for the three
languages considered in the present track (English, French, German) producing
ten different sets of ranked results. 2. The merging of the different results
based on multiple regression models using an additional validation set created
from the patent collection. 3. The exploitation of patent metadata and of the
citation structures for creating restricted initial working sets of patents and
for producing a final re-ranking regression model. As we exploit specific
metadata of the patent documents and the citation relations only at the
creation of initial working sets and during the final post ranking step, our
architecture remains generic and easy to extend.
| 2,009 | Computation and Language |
An OLAC Extension for Dravidian Languages | OLAC was founded in 2000 for creating online databases of language resources.
This paper intends to review the bottom-up distributed character of the project
and proposes an extension of the architecture for Dravidian languages. An
ontological structure is considered for effective natural language processing
(NLP) and its advantages over statistical methods are reviewed
| 2,009 | Computation and Language |
Empowering OLAC Extension using Anusaaraka and Effective text processing
using Double Byte coding | The paper reviews the hurdles while trying to implement the OLAC extension
for Dravidian / Indian languages. The paper further explores the possibilities
which could minimise or solve these problems. In this context, the Chinese
system of text processing and the anusaaraka system are scrutinised.
| 2,009 | Computation and Language |
Implementation of Rule Based Algorithm for Sandhi-Vicheda Of Compound
Hindi Words | Sandhi means to join two or more words to coin new word. Sandhi literally
means `putting together' or combining (of sounds), It denotes all combinatory
sound-changes effected (spontaneously) for ease of pronunciation.
Sandhi-vicheda describes [5] the process by which one letter (whether single or
cojoined) is broken to form two words. Part of the broken letter remains as the
last letter of the first word and part of the letter forms the first letter of
the next letter. Sandhi- Vicheda is an easy and interesting way that can give
entirely new dimension that add new way to traditional approach to Hindi
Teaching. In this paper using the Rule based algorithm we have reported an
accuracy of 60-80% depending upon the number of rules to be implemented.
| 2,009 | Computation and Language |
Reference Resolution within the Framework of Cognitive Grammar | Following the principles of Cognitive Grammar, we concentrate on a model for
reference resolution that attempts to overcome the difficulties previous
approaches, based on the fundamental assumption that all reference (independent
on the type of the referring expression) is accomplished via access to and
restructuring of domains of reference rather than by direct linkage to the
entities themselves. The model accounts for entities not explicitly mentioned
but understood in a discourse, and enables exploitation of discursive and
perceptual context to limit the set of potential referents for a given
referring expression. As the most important feature, we note that a single
mechanism is required to handle what are typically treated as diverse
phenomena. Our approach, then, provides a fresh perspective on the relations
between Cognitive Grammar and the problem of reference.
| 2,001 | Computation and Language |
Marking-up multiple views of a Text: Discourse and Reference | We describe an encoding scheme for discourse structure and reference, based
on the TEI Guidelines and the recommendations of the Corpus Encoding
Specification (CES). A central feature of the scheme is a CES-based data
architecture enabling the encoding of and access to multiple views of a
marked-up document. We describe a tool architecture that supports the encoding
scheme, and then show how we have used the encoding scheme and the tools to
perform a discourse analytic task in support of a model of global discourse
cohesion called Veins Theory (Cristea & Ide, 1998).
| 1,998 | Computation and Language |
A Common XML-based Framework for Syntactic Annotations | It is widely recognized that the proliferation of annotation schemes runs
counter to the need to re-use language resources, and that standards for
linguistic annotation are becoming increasingly mandatory. To answer this need,
we have developed a framework comprised of an abstract model for a variety of
different annotation types (e.g., morpho-syntactic tagging, syntactic
annotation, co-reference annotation, etc.), which can be instantiated in
different ways depending on the annotator's approach and goals. In this paper
we provide an overview of the framework, demonstrate its applicability to
syntactic annotation, and show how it can contribute to comparative evaluation
of parser output and diverse syntactic annotation schemes.
| 2,001 | Computation and Language |
Standards for Language Resources | This paper presents an abstract data model for linguistic annotations and its
implementation using XML, RDF and related standards; and to outline the work of
a newly formed committee of the International Standards Organization (ISO),
ISO/TC 37/SC 4 Language Resource Management, which will use this work as its
starting point. The primary motive for presenting the latter is to solicit the
participation of members of the research community to contribute to the work of
the committee.
| 2,002 | Computation and Language |
Language Models for Handwritten Short Message Services | Handwriting is an alternative method for entering texts composing Short
Message Services. However, a whole new language features the texts which are
produced. They include for instance abbreviations and other consonantal writing
which sprung up for time saving and fashion. We have collected and processed a
significant number of such handwriting SMS, and used various strategies to
tackle this challenging area of handwriting recognition. We proposed to study
more specifically three different phenomena: consonant skeleton, rebus, and
phonetic writing. For each of them, we compare the rough results produced by a
standard recognition system with those obtained when using a specific language
model.
| 2,007 | Computation and Language |
Vers la reconnaissance de mini-messages manuscrits | Handwriting is an alternative method for entering texts which composed Short
Message Services. However, a whole new language features the texts which are
produced. They include for instance abbreviations and other consonantal writing
which sprung up for time saving and fashion. We have collected and processed a
significant number of such handwritten SMS, and used various strategies to
tackle this challenging area of handwriting recognition. We proposed to study
more specifically three different phenomena: consonant skeleton, rebus, and
phonetic writing. For each of them, we compare the rough results produced by a
standard recognition system with those obtained when using a specific language
model to take care of them.
| 2,007 | Computation and Language |
Analyse en d\'ependances \`a l'aide des grammaires d'interaction | This article proposes a method to extract dependency structures from
phrase-structure level parsing with Interaction Grammars. Interaction Grammars
are a formalism which expresses interactions among words using a polarity
system. Syntactical composition is led by the saturation of polarities.
Interactions take place between constituents, but as grammars are lexicalized,
these interactions can be translated at the level of words. Dependency
relations are extracted from the parsing process: every dependency is the
consequence of a polarity saturation. The dependency relations we obtain can be
seen as a refinement of the usual dependency tree. Generally speaking, this
work sheds new light on links between phrase structure and dependency parsing.
| 2,009 | Computation and Language |
Grouping Synonyms by Definitions | We present a method for grouping the synonyms of a lemma according to its
dictionary senses. The senses are defined by a large machine readable
dictionary for French, the TLFi (Tr\'esor de la langue fran\c{c}aise
informatis\'e) and the synonyms are given by 5 synonym dictionaries (also for
French). To evaluate the proposed method, we manually constructed a gold
standard where for each (word, definition) pair and given the set of synonyms
defined for that word by the 5 synonym dictionaries, 4 lexicographers specified
the set of synonyms they judge adequate. While inter-annotator agreement ranges
on that task from 67% to at best 88% depending on the annotator pair and on the
synonym dictionary being considered, the automatic procedure we propose scores
a precision of 67% and a recall of 71%. The proposed method is compared with
related work namely, word sense disambiguation, synonym lexicon acquisition and
WordNet construction.
| 2,009 | Computation and Language |
Mathematics, Recursion, and Universals in Human Languages | There are many scientific problems generated by the multiple and conflicting
alternative definitions of linguistic recursion and human recursive processing
that exist in the literature. The purpose of this article is to make available
to the linguistic community the standard mathematical definition of recursion
and to apply it to discuss linguistic recursion. As a byproduct, we obtain an
insight into certain "soft universals" of human languages, which are related to
cognitive constructs necessary to implement mathematical reasoning, i.e.
mathematical model theory.
| 2,009 | Computation and Language |
Towards Multimodal Content Representation | Multimodal interfaces, combining the use of speech, graphics, gestures, and
facial expressions in input and output, promise to provide new possibilities to
deal with information in more effective and efficient ways, supporting for
instance: - the understanding of possibly imprecise, partial or ambiguous
multimodal input; - the generation of coordinated, cohesive, and coherent
multimodal presentations; - the management of multimodal interaction (e.g.,
task completion, adapting the interface, error prevention) by representing and
exploiting models of the user, the domain, the task, the interactive context,
and the media (e.g. text, audio, video). The present document is intended to
support the discussion on multimodal content representation, its possible
objectives and basic constraints, and how the definition of a generic
representation framework for multimodal content representation may be
approached. It takes into account the results of the Dagstuhl workshop, in
particular those of the informal working group on multimodal meaning
representation that was active during the workshop (see
http://www.dfki.de/~wahlster/Dagstuhl_Multi_Modality, Working Group 4).
| 2,002 | Computation and Language |
A Note On Higher Order Grammar | Both syntax-phonology and syntax-semantics interfaces in Higher Order Grammar
(HOG) are expressed as axiomatic theories in higher-order logic (HOL), i.e. a
language is defined entirely in terms of provability in the single logical
system. An important implication of this elegant architecture is that the
meaning of a valid expression turns out to be represented not by a single, nor
even by a few "discrete" terms (in case of ambiguity), but by a "continuous"
set of logically equivalent terms. The note is devoted to precise formulation
and proof of this observation.
| 2,009 | Computation and Language |
Ludics and its Applications to natural Language Semantics | Proofs, in Ludics, have an interpretation provided by their counter-proofs,
that is the objects they interact with. We follow the same idea by proposing
that sentence meanings are given by the counter-meanings they are opposed to in
a dialectical interaction. The conception is at the intersection of a
proof-theoretic and a game-theoretic accounts of semantics, but it enlarges
them by allowing to deal with possibly infinite processes.
| 2,009 | Computation and Language |
Evaluation of Hindi to Punjabi Machine Translation System | Machine Translation in India is relatively young. The earliest efforts date
from the late 80s and early 90s. The success of every system is judged from its
evaluation experimental results. Number of machine translation systems has been
started for development but to the best of author knowledge, no high quality
system has been completed which can be used in real applications. Recently,
Punjabi University, Patiala, India has developed Punjabi to Hindi Machine
translation system with high accuracy of about 92%. Both the systems i.e.
system under question and developed system are between same closely related
languages. Thus, this paper presents the evaluation results of Hindi to Punjabi
machine translation system. It makes sense to use same evaluation criteria as
that of Punjabi to Hindi Punjabi Machine Translation System. After evaluation,
the accuracy of the system is found to be about 95%.
| 2,009 | Computation and Language |
The Uned systems at Senseval-2 | We have participated in the SENSEVAL-2 English tasks (all words and lexical
sample) with an unsupervised system based on mutual information measured over a
large corpus (277 million words) and some additional heuristics. A supervised
extension of the system was also presented to the lexical sample task.
Our system scored first among unsupervised systems in both tasks: 56.9%
recall in all words, 40.2% in lexical sample. This is slightly worse than the
first sense heuristic for all words and 3.6% better for the lexical sample, a
strong indication that unsupervised Word Sense Disambiguation remains being a
strong challenge.
| 2,002 | Computation and Language |
Word Sense Disambiguation Based on Mutual Information and Syntactic
Patterns | This paper describes a hybrid system for WSD, presented to the English
all-words and lexical-sample tasks, that relies on two different unsupervised
approaches. The first one selects the senses according to mutual information
proximity between a context word a variant of the sense. The second heuristic
analyzes the examples of use in the glosses of the senses so that simple
syntactic patterns are inferred. This patterns are matched against the
disambiguation contexts. We show that the first heuristic obtains a precision
and recall of .58 and .35 respectively in the all words task while the second
obtains .80 and .25. The high precision obtained recommends deeper research of
the techniques. Results for the lexical sample task are also provided.
| 2,004 | Computation and Language |
Word Sense Disambiguation Using English-Spanish Aligned Phrases over
Comparable Corpora | In this paper we describe a WSD experiment based on bilingual English-Spanish
comparable corpora in which individual noun phrases have been identified and
aligned with their respective counterparts in the other language. The
evaluation of the experiment has been carried out against SemCor.
We show that, with the alignment algorithm employed, potential precision is
high (74.3%), however the coverage of the method is low (2.7%), due to
alignments being far less frequent than we expected.
Contrary to our intuition, precision does not rise consistently with the
number of alignments. The coverage is low due to several factors; there are
important domain differences, and English and Spanish are too close languages
for this approach to be able to discriminate efficiently between senses,
rendering it unsuitable for WSD, although the method may prove more productive
in machine translation.
| 2,009 | Computation and Language |
A New Computational Schema for Euphonic Conjunctions in Sanskrit
Processing | Automated language processing is central to the drive to enable facilitated
referencing of increasingly available Sanskrit E texts. The first step towards
processing Sanskrit text involves the handling of Sanskrit compound words that
are an integral part of Sanskrit texts. This firstly necessitates the
processing of euphonic conjunctions or sandhis, which are points in words or
between words, at which adjacent letters coalesce and transform. The ancient
Sanskrit grammarian Panini's codification of the Sanskrit grammar is the
accepted authority in the subject. His famed sutras or aphorisms, numbering
approximately four thousand, tersely, precisely and comprehensively codify the
rules of the grammar, including all the rules pertaining to sandhis. This work
presents a fresh new approach to processing sandhis in terms of a computational
schema. This new computational model is based on Panini's complex codification
of the rules of grammar. The model has simple beginnings and is yet powerful,
comprehensive and computationally lean.
| 2,009 | Computation and Language |
ANN-based Innovative Segmentation Method for Handwritten text in
Assamese | Artificial Neural Network (ANN) s has widely been used for recognition of
optically scanned character, which partially emulates human thinking in the
domain of the Artificial Intelligence. But prior to recognition, it is
necessary to segment the character from the text to sentences, words etc.
Segmentation of words into individual letters has been one of the major
problems in handwriting recognition. Despite several successful works all over
the work, development of such tools in specific languages is still an ongoing
process especially in the Indian context. This work explores the application of
ANN as an aid to segmentation of handwritten characters in Assamese- an
important language in the North Eastern part of India. The work explores the
performance difference obtained in applying an ANN-based dynamic segmentation
algorithm compared to projection- based static segmentation. The algorithm
involves, first training of an ANN with individual handwritten characters
recorded from different individuals. Handwritten sentences are separated out
from text using a static segmentation method. From the segmented line,
individual characters are separated out by first over segmenting the entire
line. Each of the segments thus obtained, next, is fed to the trained ANN. The
point of segmentation at which the ANN recognizes a segment or a combination of
several segments to be similar to a handwritten character, a segmentation
boundary for the character is assumed to exist and segmentation performed. The
segmented character is next compared to the best available match and the
segmentation boundary confirmed.
| 2,009 | Computation and Language |
Co-word Analysis using the Chinese Character Set | Until recently, Chinese texts could not be studied using co-word analysis
because the words are not separated by spaces in Chinese (and Japanese). A word
can be composed of one or more characters. The online availability of programs
that separate Chinese texts makes it possible to analyze them using semantic
maps. Chinese characters contain not only information, but also meaning. This
may enhance the readability of semantic maps. In this study, we analyze 58
words which occur ten or more times in the 1652 journal titles of the China
Scientific and Technical Papers and Citations Database. The word occurrence
matrix is visualized and factor-analyzed.
| 2,008 | Computation and Language |
A Discourse-based Approach in Text-based Machine Translation | This paper presents a theoretical research based approach to ellipsis
resolution in machine translation. The formula of discourse is applied in order
to resolve ellipses. The validity of the discourse formula is analyzed by
applying it to the real world text, i.e., newspaper fragments. The source text
is converted into mono-sentential discourses where complex discourses require
further dissection either directly into primitive discourses or first into
compound discourses and later into primitive ones. The procedure of dissection
needs further improvement, i.e., discovering as many primitive discourse forms
as possible. An attempt has been made to investigate new primitive discourses
or patterns from the given text.
| 2,010 | Computation and Language |
Resolution of Unidentified Words in Machine Translation | This paper presents a mechanism of resolving unidentified lexical units in
Text-based Machine Translation (TBMT). In a Machine Translation (MT) system it
is unlikely to have a complete lexicon and hence there is intense need of a new
mechanism to handle the problem of unidentified words. These unknown words
could be abbreviations, names, acronyms and newly introduced terms. We have
proposed an algorithm for the resolution of the unidentified words. This
algorithm takes discourse unit (primitive discourse) as a unit of analysis and
provides real time updates to the lexicon. We have manually applied the
algorithm to news paper fragments. Along with anaphora and cataphora
resolution, many unknown words especially names and abbreviations were updated
to the lexicon.
| 2,010 | Computation and Language |
Standards for Language Resources | The goal of this paper is two-fold: to present an abstract data model for
linguistic annotations and its implementation using XML, RDF and related
standards; and to outline the work of a newly formed committee of the
International Standards Organization (ISO), ISO/TC 37/SC 4 Language Resource
Management, which will use this work as its starting point.
| 2,001 | Computation and Language |
Active Learning for Mention Detection: A Comparison of Sentence
Selection Strategies | We propose and compare various sentence selection strategies for active
learning for the task of detecting mentions of entities. The best strategy
employs the sum of confidences of two statistical classifiers trained on
different views of the data. Our experimental results show that, compared to
the random selection strategy, this strategy reduces the amount of required
labeled training data by over 50% while achieving the same performance. The
effect is even more significant when only named mentions are considered: the
system achieves the same performance by using only 42% of the training data
required by the random selection strategy.
| 2,009 | Computation and Language |
A New Look at the Classical Entropy of Written English | A simple method for finding the entropy and redundancy of a reasonable long
sample of English text by direct computer processing and from first principles
according to Shannon theory is presented. As an example, results on the entropy
of the English language have been obtained based on a total of 20.3 million
characters of written English, considering symbols from one to five hundred
characters in length. Besides a more realistic value of the entropy of English,
a new perspective on some classic entropy-related concepts is presented. This
method can also be extended to other Latin languages. Some implications for
practical applications such as plagiarism-detection software, and the minimum
number of words that should be used in social Internet network messaging, are
discussed.
| 2,009 | Computation and Language |
Automated languages phylogeny from Levenshtein distance | Languages evolve over time in a process in which reproduction, mutation and
extinction are all possible, similar to what happens to living organisms. Using
this similarity it is possible, in principle, to build family trees which show
the degree of relatedness between languages.
The method used by modern glottochronology, developed by Swadesh in the
1950s, measures distances from the percentage of words with a common historical
origin. The weak point of this method is that subjective judgment plays a
relevant role.
Recently we proposed an automated method that avoids the subjectivity, whose
results can be replicated by studies that use the same database and that
doesn't require a specific linguistic knowledge. Moreover, the method allows a
quick comparison of a large number of languages.
We applied our method to the Indo-European and Austronesian families,
considering in both cases, fifty different languages. The resulting trees are
similar to those of previous studies, but with some important differences in
the position of few languages and subgroups. We believe that these differences
carry new information on the structure of the tree and on the phylogenetic
relationships within families.
| 2,012 | Computation and Language |
Automated words stability and languages phylogeny | The idea of measuring distance between languages seems to have its roots in
the work of the French explorer Dumont D'Urville (D'Urville 1832). He collected
comparative words lists of various languages during his voyages aboard the
Astrolabe from 1826 to1829 and, in his work about the geographical division of
the Pacific, he proposed a method to measure the degree of relation among
languages. The method used by modern glottochronology, developed by Morris
Swadesh in the 1950s (Swadesh 1952), measures distances from the percentage of
shared cognates, which are words with a common historical origin. Recently, we
proposed a new automated method which uses normalized Levenshtein distance
among words with the same meaning and averages on the words contained in a
list. Another classical problem in glottochronology is the study of the
stability of words corresponding to different meanings. Words, in fact, evolve
because of lexical changes, borrowings and replacement at a rate which is not
the same for all of them. The speed of lexical evolution is different for
different meanings and it is probably related to the frequency of use of the
associated words (Pagel et al. 2007). This problem is tackled here by an
automated methodology only based on normalized Levenshtein distance.
| 2,009 | Computation and Language |
Measuring the Meaning of Words in Contexts: An automated analysis of
controversies about Monarch butterflies, Frankenfoods, and stem cells | Co-words have been considered as carriers of meaning across different domains
in studies of science, technology, and society. Words and co-words, however,
obtain meaning in sentences, and sentences obtain meaning in their contexts of
use. At the science/society interface, words can be expected to have different
meanings: the codes of communication that provide meaning to words differ on
the varying sides of the interface. Furthermore, meanings and interfaces may
change over time. Given this structuring of meaning across interfaces and over
time, we distinguish between metaphors and diaphors as reflexive mechanisms
that facilitate the translation between contexts. Our empirical focus is on
three recent scientific controversies: Monarch butterflies, Frankenfoods, and
stem-cell therapies. This study explores new avenues that relate the study of
co-word analysis in context with the sociological quest for the analysis and
processing of meaning.
| 2,006 | Computation and Language |
Standardization of the formal representation of lexical information for
NLP | A survey of dictionary models and formats is presented as well as a
presentation of corresponding recent standardisation activities.
| 2,010 | Computation and Language |
Acquisition d'informations lexicales \`a partir de corpus C\'edric
Messiant et Thierry Poibeau | This paper is about automatic acquisition of lexical information from
corpora, especially subcategorization acquisition.
| 2,009 | Computation and Language |
Hierarchies in Dictionary Definition Space | A dictionary defines words in terms of other words. Definitions can tell you
the meanings of words you don't know, but only if you know the meanings of the
defining words. How many words do you need to know (and which ones) in order to
be able to learn all the rest from definitions? We reduced dictionaries to
their "grounding kernels" (GKs), about 10% of the dictionary, from which all
the other words could be defined. The GK words turned out to have
psycholinguistic correlates: they were learned at an earlier age and more
concrete than the rest of the dictionary. But one can compress still more: the
GK turns out to have internal structure, with a strongly connected "kernel
core" (KC) and a surrounding layer, from which a hierarchy of definitional
distances can be derived, all the way out to the periphery of the full
dictionary. These definitional distances, too, are correlated with
psycholinguistic variables (age of acquisition, concreteness, imageability,
oral and written frequency) and hence perhaps with the "mental lexicon" in each
of our heads.
| 2,009 | Computation and Language |
Lexical evolution rates by automated stability measure | Phylogenetic trees can be reconstructed from the matrix which contains the
distances between all pairs of languages in a family. Recently, we proposed a
new method which uses normalized Levenshtein distances among words with same
meaning and averages on all the items of a given list. Decisions about the
number of items in the input lists for language comparison have been debated
since the beginning of glottochronology. The point is that words associated to
some of the meanings have a rapid lexical evolution. Therefore, a large
vocabulary comparison is only apparently more accurate then a smaller one since
many of the words do not carry any useful information. In principle, one should
find the optimal length of the input lists studying the stability of the
different items. In this paper we tackle the problem with an automated
methodology only based on our normalized Levenshtein distance. With this
approach, the program of an automated reconstruction of languages relationships
is completed.
| 2,015 | Computation and Language |
Measures of lexical distance between languages | The idea of measuring distance between languages seems to have its roots in
the work of the French explorer Dumont D'Urville \cite{Urv}. He collected
comparative words lists of various languages during his voyages aboard the
Astrolabe from 1826 to 1829 and, in his work about the geographical division of
the Pacific, he proposed a method to measure the degree of relation among
languages. The method used by modern glottochronology, developed by Morris
Swadesh in the 1950s, measures distances from the percentage of shared
cognates, which are words with a common historical origin. Recently, we
proposed a new automated method which uses normalized Levenshtein distance
among words with the same meaning and averages on the words contained in a
list. Recently another group of scholars \cite{Bak, Hol} proposed a refined of
our definition including a second normalization. In this paper we compare the
information content of our definition with the refined version in order to
decide which of the two can be applied with greater success to resolve
relationships among languages.
| 2,015 | Computation and Language |
Parsing of part-of-speech tagged Assamese Texts | A natural language (or ordinary language) is a language that is spoken,
written, or signed by humans for general-purpose communication, as
distinguished from formal languages (such as computer-programming languages or
the "languages" used in the study of formal logic). The computational
activities required for enabling a computer to carry out information processing
using natural language is called natural language processing. We have taken
Assamese language to check the grammars of the input sentence. Our aim is to
produce a technique to check the grammatical structures of the sentences in
Assamese text. We have made grammar rules by analyzing the structures of
Assamese sentences. Our parsing program finds the grammatical errors, if any,
in the Assamese sentence. If there is no error, the program will generate the
parse tree for the Assamese sentence
| 2,009 | Computation and Language |
Representing human and machine dictionaries in Markup languages | In this chapter we present the main issues in representing machine readable
dictionaries in XML, and in particular according to the Text Encoding
Dictionary (TEI) guidelines.
| 2,010 | Computation and Language |
A Survey of Paraphrasing and Textual Entailment Methods | Paraphrasing methods recognize, generate, or extract phrases, sentences, or
longer natural language expressions that convey almost the same information.
Textual entailment methods, on the other hand, recognize, generate, or extract
pairs of natural language expressions, such that a human who reads (and trusts)
the first element of a pair would most likely infer that the other element is
also true. Paraphrasing can be seen as bidirectional textual entailment and
methods from the two areas are often similar. Both kinds of methods are useful,
at least in principle, in a wide range of natural language processing
applications, including question answering, summarization, text generation, and
machine translation. We summarize key ideas from the two areas by considering
in turn recognition, generation, and extraction methods, also pointing to
prominent articles and resources.
| 2,010 | Computation and Language |
Speech Recognition Oriented Vowel Classification Using Temporal Radial
Basis Functions | The recent resurgence of interest in spatio-temporal neural network as speech
recognition tool motivates the present investigation. In this paper an approach
was developed based on temporal radial basis function "TRBF" looking to many
advantages: few parameters, speed convergence and time invariance. This
application aims to identify vowels taken from natural speech samples from the
Timit corpus of American speech. We report a recognition accuracy of 98.06
percent in training and 90.13 in test on a subset of 6 vowel phonemes, with the
possibility to expend the vowel sets in future.
| 2,009 | Computation and Language |
Syllable Analysis to Build a Dictation System in Telugu language | In recent decades, Speech interactive systems gained increasing importance.
To develop Dictation System like Dragon for Indian languages it is most
important to adapt the system to a speaker with minimum training. In this paper
we focus on the importance of creating speech database at syllable units and
identifying minimum text to be considered while training any speech recognition
system. There are systems developed for continuous speech recognition in
English and in few Indian languages like Hindi and Tamil. This paper gives the
statistical details of syllables in Telugu and its use in minimizing the search
space during recognition of speech. The minimum words that cover maximum
syllables are identified. This words list can be used for preparing a small
text which can be used for collecting speech sample while training the
dictation system. The results are plotted for frequency of syllables and the
number of syllables in each word. This approach is applied on the CIIL Mysore
text corpus which is of 3 million words.
| 2,009 | Computation and Language |
Speech Recognition by Machine, A Review | This paper presents a brief survey on Automatic Speech Recognition and
discusses the major themes and advances made in the past 60 years of research,
so as to provide a technological perspective and an appreciation of the
fundamental progress that has been accomplished in this important area of
speech communication. After years of research and development the accuracy of
automatic speech recognition remains one of the important research challenges
(e.g., variations of the context, speakers, and environment).The design of
Speech Recognition system requires careful attentions to the following issues:
Definition of various types of speech classes, speech representation, feature
extraction techniques, speech classifiers, database and performance evaluation.
The problems that are existing in ASR and the various techniques to solve these
problems constructed by various research workers have been presented in a
chronological order. Hence authors hope that this work shall be a contribution
in the area of speech recognition. The objective of this review paper is to
summarize and compare some of the well known methods used in various stages of
speech recognition system and identify research topic and applications which
are at the forefront of this exciting and challenging field.
| 2,009 | Computation and Language |
Sentence Simplification Aids Protein-Protein Interaction Extraction | Accurate systems for extracting Protein-Protein Interactions (PPIs)
automatically from biomedical articles can help accelerate biomedical research.
Biomedical Informatics researchers are collaborating to provide metaservices
and advance the state-of-art in PPI extraction. One problem often neglected by
current Natural Language Processing systems is the characteristic complexity of
the sentences in biomedical literature. In this paper, we report on the impact
that automatic simplification of sentences has on the performance of a
state-of-art PPI extraction system, showing a substantial improvement in recall
(8%) when the sentence simplification method is applied, without significant
impact to precision.
| 2,009 | Computation and Language |
Towards Effective Sentence Simplification for Automatic Processing of
Biomedical Text | The complexity of sentences characteristic to biomedical articles poses a
challenge to natural language parsers, which are typically trained on
large-scale corpora of non-technical text. We propose a text simplification
process, bioSimplify, that seeks to reduce the complexity of sentences in
biomedical abstracts in order to improve the performance of syntactic parsers
on the processed sentences. Syntactic parsing is typically one of the first
steps in a text mining pipeline. Thus, any improvement in performance would
have a ripple effect over all processing steps. We evaluated our method using a
corpus of biomedical sentences annotated with syntactic links. Our empirical
results show an improvement of 2.90% for the Charniak-McClosky parser and of
4.23% for the Link Grammar parser when processing simplified sentences rather
than the original sentences in the corpus.
| 2,009 | Computation and Language |
\'Etude et traitement automatique de l'anglais du XVIIe si\`ecle :
outils morphosyntaxiques et dictionnaires | In this article, we record the main linguistic differences or singularities
of 17th century English, analyse them morphologically and syntactically and
propose equivalent forms in contemporary English. We show how 17th century
texts may be transcribed into modern English, combining the use of electronic
dictionaries with rules of transcription implemented as transducers. Apr\`es
avoir expos\'e la constitution du corpus, nous recensons les principales
diff\'erences ou particularit\'es linguistiques de la langue anglaise du XVIIe
si\`ecle, les analysons du point de vue morphologique et syntaxique et
proposons des \'equivalents en anglais contemporain (AC). Nous montrons comment
nous pouvons effectuer une transcription automatique de textes anglais du XVIIe
si\`ecle en anglais moderne, en combinant l'utilisation de dictionnaires
\'electroniques avec des r\`egles de transcriptions impl\'ement\'ees sous forme
de transducteurs.
| 2,010 | Computation and Language |
"Mind your p's and q's": or the peregrinations of an apostrophe in 17th
Century English | If the use of the apostrophe in contemporary English often marks the Saxon
genitive, it may also indicate the omission of one or more let-ters. Some
writers (wrongly?) use it to mark the plural in symbols or abbreviations,
visual-ised thanks to the isolation of the morpheme "s". This punctuation mark
was imported from the Continent in the 16th century. During the 19th century
its use was standardised. However the rules of its usage still seem problematic
to many, including literate speakers of English. "All too often, the apostrophe
is misplaced", or "errant apostrophes are springing up every-where" is a
complaint that Internet users fre-quently come across when visiting grammar
websites. Many of them detail its various uses and misuses, and attempt to
correct the most common mistakes about it, especially its mis-use in the
plural, called greengrocers' apostro-phes and humorously misspelled
"greengro-cers apostrophe's". While studying English travel accounts published
in the seventeenth century, we noticed that the different uses of this symbol
may accompany various models of metaplasms. We were able to highlight the
linguistic variations of some lexemes, and trace the origin of modern grammar
rules gov-erning its usage.
| 2,010 | Computation and Language |
Recognition and translation Arabic-French of Named Entities: case of the
Sport places | The recognition of Arabic Named Entities (NE) is a problem in different
domains of Natural Language Processing (NLP) like automatic translation.
Indeed, NE translation allows the access to multilingual in-formation. This
translation doesn't always lead to expected result especially when NE contains
a person name. For this reason and in order to ameliorate translation, we can
transliterate some part of NE. In this context, we propose a method that
integrates translation and transliteration together. We used the linguis-tic
NooJ platform that is based on local grammars and transducers. In this paper,
we focus on sport domain. We will firstly suggest a refinement of the
typological model presented at the MUC Conferences we will describe the
integration of an Arabic transliteration module into translation system.
Finally, we will detail our method and give the results of the evaluation.
| 2,010 | Computation and Language |
Morphological study of Albanian words, and processing with NooJ | We are developing electronic dictionaries and transducers for the automatic
processing of the Albanian Language. We will analyze the words inside a linear
segment of text. We will also study the relationship between units of sense and
units of form. The composition of words takes different forms in Albanian. We
have found that morphemes are frequently concatenated or simply juxtaposed or
contracted. The inflected grammar of NooJ allows constructing the dictionaries
of flexed forms (declensions or conjugations). The diversity of word structures
requires tools to identify words created by simple concatenation, or to treat
contractions. The morphological tools of NooJ allow us to create grammatical
tools to represent and treat these phenomena. But certain problems exceed the
morphological analysis and must be represented by syntactical grammars.
| 2,010 | Computation and Language |
Approximations to the MMI criterion and their effect on lattice-based
MMI | Maximum mutual information (MMI) is a model selection criterion used for
hidden Markov model (HMM) parameter estimation that was developed more than
twenty years ago as a discriminative alternative to the maximum likelihood
criterion for HMM-based speech recognition. It has been shown in the speech
recognition literature that parameter estimation using the current MMI
paradigm, lattice-based MMI, consistently outperforms maximum likelihood
estimation, but this is at the expense of undesirable convergence properties.
In particular, recognition performance is sensitive to the number of times that
the iterative MMI estimation algorithm, extended Baum-Welch, is performed. In
fact, too many iterations of extended Baum-Welch will lead to degraded
performance, despite the fact that the MMI criterion improves at each
iteration. This phenomenon is at variance with the analogous behavior of
maximum likelihood estimation -- at least for the HMMs used in speech
recognition -- and it has previously been attributed to `over fitting'. In this
paper, we present an analysis of lattice-based MMI that demonstrates, first of
all, that the asymptotic behavior of lattice-based MMI is much worse than was
previously understood, i.e. it does not appear to converge at all, and, second
of all, that this is not due to `over fitting'. Instead, we demonstrate that
the `over fitting' phenomenon is the result of standard methodology that
exacerbates the poor behavior of two key approximations in the lattice-based
MMI machinery. We also demonstrate that if we modify the standard methodology
to improve the validity of these approximations, then the convergence
properties of lattice-based MMI become benign without sacrificing improvements
to recognition accuracy.
| 2,010 | Computation and Language |
On Event Structure in the Torn Dress | Using Pustejovsky's "The Syntax of Event Structure" and Fong's "On Mending a
Torn Dress" we give a glimpse of a Pustejovsky-like analysis to some example
sentences in Fong. We attempt to give a framework for semantics to the noun
phrases and adverbs as appropriate as well as the lexical entries for all words
in the examples and critique both papers in light of our findings and
difficulties.
| 2,010 | Computation and Language |
Towards a Heuristic Categorization of Prepositional Phrases in English
with WordNet | This document discusses an approach and its rudimentary realization towards
automatic classification of PPs; the topic, that has not received as much
attention in NLP as NPs and VPs. The approach is a rule-based heuristics
outlined in several levels of our research. There are 7 semantic categories of
PPs considered in this document that we are able to classify from an annotated
corpus.
| 2,010 | Computation and Language |
Thai Rhetorical Structure Analysis | Rhetorical structure analysis (RSA) explores discourse relations among
elementary discourse units (EDUs) in a text. It is very useful in many text
processing tasks employing relationships among EDUs such as text understanding,
summarization, and question-answering. Thai language with its distinctive
linguistic characteristics requires a unique technique. This article proposes
an approach for Thai rhetorical structure analysis. First, EDUs are segmented
by two hidden Markov models derived from syntactic rules. A rhetorical
structure tree is constructed from a clustering technique with its similarity
measure derived from Thai semantic rules. Then, a decision tree whose features
derived from the semantic rules is used to determine discourse relations.
| 2,010 | Computation and Language |
Co-channel Interference Cancellation for Space-Time Coded OFDM Systems
Using Adaptive Beamforming and Null Deepening | Combined with space-time coding, the orthogonal frequency division
multiplexing (OFDM) system explores space diversity. It is a potential scheme
to offer spectral efficiency and robust high data rate transmissions over
frequency-selective fading channel. However, space-time coding impairs the
system ability to suppress interferences as the signals transmitted from two
transmit antennas are superposed and interfered at the receiver antennas. In
this paper, we developed an adaptive beamforming based on least mean squared
error algorithm and null deepening to combat co-channel interference (CCI) for
the space-time coded OFDM (STC-OFDM) system. To illustrate the performance of
the presented approach, it is compared to the null steering beamformer which
requires a prior knowledge of directions of arrival (DOAs). The structure of
space-time decoders are preserved although there is the use of beamformers
before decoding. By incorporating the proposed beamformer as a CCI canceller in
the STC-OFDM systems, the performance improvement is achieved as shown in the
simulation results.
| 2,010 | Computation and Language |
Syntactic Topic Models | The syntactic topic model (STM) is a Bayesian nonparametric model of language
that discovers latent distributions of words (topics) that are both
semantically and syntactically coherent. The STM models dependency parsed
corpora where sentences are grouped into documents. It assumes that each word
is drawn from a latent topic chosen by combining document-level features and
the local syntactic context. Each document has a distribution over latent
topics, as in topic models, which provides the semantic consistency. Each
element in the dependency parse tree also has a distribution over the topics of
its children, as in latent-state syntax models, which provides the syntactic
consistency. These distributions are convolved so that the topic of each word
is likely under both its document and syntactic context. We derive a fast
posterior inference algorithm based on variational methods. We report
qualitative and quantitative studies on both synthetic data and hand-parsed
documents. We show that the STM is a more predictive model of language than
current models based only on syntax or only on topics.
| 2,010 | Computation and Language |
SLAM : Solutions lexicales automatique pour m\'etaphores | This article presents SLAM, an Automatic Solver for Lexical Metaphors like
?d\'eshabiller* une pomme? (to undress* an apple). SLAM calculates a
conventional solution for these productions. To carry on it, SLAM has to
intersect the paradigmatic axis of the metaphorical verb ?d\'eshabiller*?,
where ?peler? (?to peel?) comes closer, with a syntagmatic axis that comes from
a corpus where ?peler une pomme? (to peel an apple) is semantically and
syntactically regular. We test this model on DicoSyn, which is a ?small world?
network of synonyms, to compute the paradigmatic axis and on Frantext.20, a
French corpus, to compute the syntagmatic axis. Further, we evaluate the model
with a sample of an experimental corpus of the database of Flexsem
| 2,009 | Computation and Language |
Why has (reasonably accurate) Automatic Speech Recognition been so hard
to achieve? | Hidden Markov models (HMMs) have been successfully applied to automatic
speech recognition for more than 35 years in spite of the fact that a key HMM
assumption -- the statistical independence of frames -- is obviously violated
by speech data. In fact, this data/model mismatch has inspired many attempts to
modify or replace HMMs with alternative models that are better able to take
into account the statistical dependence of frames. However it is fair to say
that in 2010 the HMM is the consensus model of choice for speech recognition
and that HMMs are at the heart of both commercially available products and
contemporary research systems. In this paper we present a preliminary
exploration aimed at understanding how speech data depart from HMMs and what
effect this departure has on the accuracy of HMM-based speech recognition. Our
analysis uses standard diagnostic tools from the field of statistics --
hypothesis testing, simulation and resampling -- which are rarely used in the
field of speech recognition. Our main result, obtained by novel manipulations
of real and resampled data, demonstrates that real data have statistical
dependency and that this dependency is responsible for significant numbers of
recognition errors. We also demonstrate, using simulation and resampling, that
if we `remove' the statistical dependency from data, then the resulting
recognition error rates become negligible. Taken together, these results
suggest that a better understanding of the structure of the statistical
dependency in speech data is a crucial first step towards improving HMM-based
speech recognition.
| 2,010 | Computation and Language |
Change of word types to word tokens ratio in the course of translation
(based on Russian translations of K. Vonnegut novels) | The article provides lexical statistical analysis of K. Vonnegut's two novels
and their Russian translations. It is found out that there happen some changes
between the speed of word types and word tokens ratio change in the source and
target texts. The author hypothesizes that these changes are typical for
English-Russian translations, and moreover, they represent an example of
Baker's translation feature of levelling out.
| 2,010 | Computation and Language |
Linguistic Geometries for Unsupervised Dimensionality Reduction | Text documents are complex high dimensional objects. To effectively visualize
such data it is important to reduce its dimensionality and visualize the low
dimensional embedding as a 2-D or 3-D scatter plot. In this paper we explore
dimensionality reduction methods that draw upon domain knowledge in order to
achieve a better low dimensional embedding and visualization of documents. We
consider the use of geometries specified manually by an expert, geometries
derived automatically from corpus statistics, and geometries computed from
linguistic resources.
| 2,010 | Computation and Language |
From Frequency to Meaning: Vector Space Models of Semantics | Computers understand very little of the meaning of human language. This
profoundly limits our ability to give instructions to computers, the ability of
computers to explain their actions to us, and the ability of computers to
analyse and process text. Vector space models (VSMs) of semantics are beginning
to address these limits. This paper surveys the use of VSMs for semantic
processing of text. We organize the literature on VSMs according to the
structure of the matrix in a VSM. There are currently three broad classes of
VSMs, based on term-document, word-context, and pair-pattern matrices, yielding
three classes of applications. We survey a broad range of applications in these
three categories and we take a detailed look at a specific open source project
in each category. Our goal in this survey is to show the breadth of
applications of VSMs for semantics, to provide a new perspective on VSMs for
those who are already familiar with the area, and to provide pointers into the
literature for those who are less familiar with the field.
| 2,010 | Computation and Language |
Automatic derivation of domain terms and concept location based on the
analysis of the identifiers | Developers express the meaning of the domain ideas in specifically selected
identifiers and comments that form the target implemented code. Software
maintenance requires knowledge and understanding of the encoded ideas. This
paper presents a way how to create automatically domain vocabulary. Knowledge
of domain vocabulary supports the comprehension of a specific domain for later
code maintenance or evolution. We present experiments conducted in two selected
domains: application servers and web frameworks. Knowledge of domain terms
enables easy localization of chunks of code that belong to a certain term. We
consider these chunks of code as "concepts" and their placement in the code as
"concept location". Application developers may also benefit from the obtained
domain terms. These terms are parts of speech that characterize a certain
concept. Concepts are encoded in "classes" (OO paradigm) and the obtained
vocabulary of terms supports the selection and the comprehension of the class'
appropriate identifiers. We measured the following software products with our
tool: JBoss, JOnAS, GlassFish, Tapestry, Google Web Toolkit and Echo2.
| 2,010 | Computation and Language |
A Computational Algorithm based on Empirical Analysis, that Composes
Sanskrit Poetry | Poetry-writing in Sanskrit is riddled with problems for even those who know
the language well. This is so because the rules that govern Sanskrit prosody
are numerous and stringent. We propose a computational algorithm that converts
prose given as E-text into poetry in accordance with the metrical rules of
Sanskrit prosody, simultaneously taking care to ensure that sandhi or euphonic
conjunction, which is compulsory in verse, is handled. The algorithm is
considerably speeded up by a novel method of reducing the target search
database. The algorithm further gives suggestions to the poet in case what
he/she has given as the input prose is impossible to fit into any allowed
metrical format. There is also an interactive component of the algorithm by
which the algorithm interacts with the poet to resolve ambiguities. In
addition, this unique work, which provides a solution to a problem that has
never been addressed before, provides a simple yet effective speech recognition
interface that would help the visually impaired dictate words in E-text, which
is in turn versified by our Poetry Composer Engine.
| 2,010 | Computation and Language |
Les Entit\'es Nomm\'ees : usage et degr\'es de pr\'ecision et de
d\'esambigu\"isation | The recognition and classification of Named Entities (NER) are regarded as an
important component for many Natural Language Processing (NLP) applications.
The classification is usually made by taking into account the immediate context
in which the NE appears. In some cases, this immediate context does not allow
getting the right classification. We show in this paper that the use of an
extended syntactic context and large-scale resources could be very useful in
the NER task.
| 2,007 | Computation and Language |
Mathematical Foundations for a Compositional Distributional Model of
Meaning | We propose a mathematical framework for a unification of the distributional
theory of meaning in terms of vector space models, and a compositional theory
for grammatical types, for which we rely on the algebra of Pregroups,
introduced by Lambek. This mathematical framework enables us to compute the
meaning of a well-typed sentence from the meanings of its constituents.
Concretely, the type reductions of Pregroups are `lifted' to morphisms in a
category, a procedure that transforms meanings of constituents into a meaning
of the (well-typed) whole. Importantly, meanings of whole sentences live in a
single space, independent of the grammatical structure of the sentence. Hence
the inner-product can be used to compare meanings of arbitrary sentences, as it
is for comparing the meanings of words in the distributional model. The
mathematical structure we employ admits a purely diagrammatic calculus which
exposes how the information flows between the words in a sentence in order to
make up the meaning of the whole sentence. A variation of our `categorical
model' which involves constraining the scalars of the vector spaces to the
semiring of Booleans results in a Montague-style Boolean-valued semantics.
| 2,010 | Computation and Language |
La repr\'esentation formelle des concepts spatiaux dans la langue | In this chapter, we assume that systematically studying spatial markers
semantics in language provides a means to reveal fundamental properties and
concepts characterizing conceptual representations of space. We propose a
formal system accounting for the properties highlighted by the linguistic
analysis, and we use these tools for representing the semantic content of
several spatial relations of French. The first part presents a semantic
analysis of the expression of space in French aiming at describing the
constraints that formal representations have to take into account. In the
second part, after presenting the structure of our formal system, we set out
its components. A commonsense geometry is sketched out and several functional
and pragmatic spatial concepts are formalized. We take a special attention in
showing that these concepts are well suited to representing the semantic
content of several prepositions of French ('sur' (on), 'dans' (in), 'devant'
(in front of), 'au-dessus' (above)), and in illustrating the inferential
adequacy of these representations.
| 1,997 | Computation and Language |
Les entit\'es spatiales dans la langue : \'etude descriptive, formelle
et exp\'erimentale de la cat\'egorisation | While previous linguistic and psycholinguistic research on space has mainly
analyzed spatial relations, the studies reported in this paper focus on how
language distinguishes among spatial entities. Descriptive and experimental
studies first propose a classification of entities, which accounts for both
static and dynamic space, has some cross-linguistic validity, and underlies
adults' cognitive processing. Formal and computational analyses then introduce
theoretical elements aiming at modelling these categories, while fulfilling
various properties of formal ontologies (generality, parsimony, coherence...).
This formal framework accounts, in particular, for functional dependences among
entities underlying some part-whole descriptions. Finally, developmental
research shows that language-specific properties have a clear impact on how
children talk about space. The results suggest some cross-linguistic
variability in children's spatial representations from an early age onwards,
bringing into question models in which general cognitive capacities are the
only determinants of spatial cognition during the course of development.
| 2,005 | Computation and Language |
Learning Recursive Segments for Discourse Parsing | Automatically detecting discourse segments is an important preliminary step
towards full discourse parsing. Previous research on discourse segmentation
have relied on the assumption that elementary discourse units (EDUs) in a
document always form a linear sequence (i.e., they can never be nested).
Unfortunately, this assumption turns out to be too strong, for some theories of
discourse like SDRT allows for nested discourse units. In this paper, we
present a simple approach to discourse segmentation that is able to produce
nested EDUs. Our approach builds on standard multi-class classification
techniques combined with a simple repairing heuristic that enforces global
coherence. Our system was developed and evaluated on the first round of
annotations provided by the French Annodis project (an ongoing effort to create
a discourse bank for French). Cross-validated on only 47 documents (1,445
EDUs), our system achieves encouraging performance results with an F-score of
73% for finding EDUs.
| 2,010 | Computation and Language |
Statistical Physics for Natural Language Processing | This paper has been withdrawn by the author.
| 2,015 | Computation and Language |
Displacement Calculus | The Lambek calculus provides a foundation for categorial grammar in the form
of a logic of concatenation. But natural language is characterized by
dependencies which may also be discontinuous. In this paper we introduce the
displacement calculus, a generalization of Lambek calculus, which preserves its
good proof-theoretic properties while embracing discontinuiity and subsuming
it. We illustrate linguistic applications and prove Cut-elimination, the
subformula property, and decidability
| 2,010 | Computation and Language |
Punctuation effects in English and Esperanto texts | A statistical physics study of punctuation effects on sentence lengths is
presented for written texts: {\it Alice in wonderland} and {\it Through a
looking glass}. The translation of the first text into esperanto is also
considered as a test for the role of punctuation in defining a style, and for
contrasting natural and artificial, but written, languages. Several log-log
plots of the sentence length-rank relationship are presented for the major
punctuation marks. Different power laws are observed with characteristic
exponents. The exponent can take a value much less than unity ($ca.$ 0.50 or
0.30) depending on how a sentence is defined. The texts are also mapped into
time series based on the word frequencies. The quantitative differences between
the original and translated texts are very minutes, at the exponent level. It
is argued that sentences seem to be more reliable than word distributions in
discussing an author style.
| 2,010 | Computation and Language |
Morphonette: a morphological network of French | This paper describes in details the first version of Morphonette, a new
French morphological resource and a new radically lexeme-based method of
morphological analysis. This research is grounded in a paradigmatic conception
of derivational morphology where the morphological structure is a structure of
the entire lexicon and not one of the individual words it contains. The
discovery of this structure relies on a measure of morphological similarity
between words, on formal analogy and on the properties of two morphological
paradigms:
| 2,010 | Computation and Language |
The Lambek-Grishin calculus is NP-complete | The Lambek-Grishin calculus LG is the symmetric extension of the
non-associative Lambek calculus NL. In this paper we prove that the
derivability problem for LG is NP-complete.
| 2,010 | Computation and Language |
Network analysis of a corpus of undeciphered Indus civilization
inscriptions indicates syntactic organization | Archaeological excavations in the sites of the Indus Valley civilization
(2500-1900 BCE) in Pakistan and northwestern India have unearthed a large
number of artifacts with inscriptions made up of hundreds of distinct signs. To
date there is no generally accepted decipherment of these sign sequences and
there have been suggestions that the signs could be non-linguistic. Here we
apply complex network analysis techniques to a database of available Indus
inscriptions, with the aim of detecting patterns indicative of syntactic
organization. Our results show the presence of patterns, e.g., recursive
structures in the segmentation trees of the sequences, that suggest the
existence of a grammar underlying these inscriptions.
| 2,011 | Computation and Language |
Using Soft Constraints To Learn Semantic Models Of Descriptions Of
Shapes | The contribution of this paper is to provide a semantic model (using soft
constraints) of the words used by web-users to describe objects in a language
game; a game in which one user describes a selected object of those composing
the scene, and another user has to guess which object has been described. The
given description needs to be non ambiguous and accurate enough to allow other
users to guess the described shape correctly.
To build these semantic models the descriptions need to be analyzed to
extract the syntax and words' classes used. We have modeled the meaning of
these descriptions using soft constraints as a way for grounding the meaning.
The descriptions generated by the system took into account the context of the
object to avoid ambiguous descriptions, and allowed users to guess the
described object correctly 72% of the times.
| 2,010 | Computation and Language |
Quantitative parametrization of texts written by Ivan Franko: An attempt
of the project | In the article, the project of quantitative parametrization of all texts by
Ivan Franko is manifested. It can be made only by using modern computer
techniques after the frequency dictionaries for all Franko's works are
compiled. The paper describes the application spheres, methodology, stages,
principles and peculiarities in the compilation of the frequency dictionary of
the second half of the 19th century - the beginning of the 20th century. The
relation between the Ivan Franko frequency dictionary, explanatory dictionary
of writer's language and text corpus is discussed.
| 2,010 | Computation and Language |
A generic tool to generate a lexicon for NLP from Lexicon-Grammar tables | Lexicon-Grammar tables constitute a large-coverage syntactic lexicon but they
cannot be directly used in Natural Language Processing (NLP) applications
because they sometimes rely on implicit information. In this paper, we
introduce LGExtract, a generic tool for generating a syntactic lexicon for NLP
from the Lexicon-Grammar tables. It is based on a global table that contains
undefined information and on a unique extraction script including all
operations to be performed for all tables. We also present an experiment that
has been conducted to generate a new lexicon of French verbs and predicative
nouns.
| 2,008 | Computation and Language |
Ivan Franko's novel Dlja domashnjoho ohnyshcha (For the Hearth) in the
light of the frequency dictionary | In the article, the methodology and the principles of the compilation of the
Frequency dictionary for Ivan Franko's novel Dlja domashnjoho ohnyshcha (For
the Hearth) are described. The following statistical parameters of the novel
vocabulary are obtained: variety, exclusiveness, concentration indexes,
correlation between word rank and text coverage, etc. The main quantitative
characteristics of Franko's novels Perekhresni stezhky (The Cross-Paths) and
Dlja domashnjoho ohnyshcha are compared on the basis of their frequency
dictionaries.
| 2,010 | Computation and Language |
Segmentation and Nodal Points in Narrative: Study of Multiple Variations
of a Ballad | The Lady Maisry ballads afford us a framework within which to segment a
storyline into its major components. Segments and as a consequence nodal points
are discussed for nine different variants of the Lady Maisry story of a (young)
woman being burnt to death by her family, on account of her becoming pregnant
by a foreign personage. We motivate the importance of nodal points in textual
and literary analysis. We show too how the openings of the nine variants can be
analyzed comparatively, and also the conclusions of the ballads.
| 2,010 | Computation and Language |
Offline Arabic Handwriting Recognition Using Artificial Neural Network | The ambition of a character recognition system is to transform a text
document typed on paper into a digital format that can be manipulated by word
processor software Unlike other languages, Arabic has unique features, while
other language doesn't have, from this language these are seven or eight
language such as ordo, jewie and Persian writing, Arabic has twenty eight
letters, each of which can be linked in three different ways or separated
depending on the case. The difficulty of the Arabic handwriting recognition is
that, the accuracy of the character recognition which affects on the accuracy
of the word recognition, in additional there is also two or three from for each
character, the suggested solution by using artificial neural network can solve
the problem and overcome the difficulty of Arabic handwriting recognition.
| 2,010 | Computation and Language |
Fuzzy Modeling and Natural Language Processing for Panini's Sanskrit
Grammar | Indian languages have long history in World Natural languages. Panini was the
first to define Grammar for Sanskrit language with about 4000 rules in fifth
century. These rules contain uncertainty information. It is not possible to
Computer processing of Sanskrit language with uncertain information. In this
paper, fuzzy logic and fuzzy reasoning are proposed to deal to eliminate
uncertain information for reasoning with Sanskrit grammar. The Sanskrit
language processing is also discussed in this paper.
| 2,010 | Computation and Language |
The probabilistic analysis of language acquisition: Theoretical,
computational, and experimental analysis | There is much debate over the degree to which language learning is governed
by innate language-specific biases, or acquired through cognition-general
principles. Here we examine the probabilistic language acquisition hypothesis
on three levels: We outline a novel theoretical result showing that it is
possible to learn the exact generative model underlying a wide class of
languages, purely from observing samples of the language. We then describe a
recently proposed practical framework, which quantifies natural language
learnability, allowing specific learnability predictions to be made for the
first time. In previous work, this framework was used to make learnability
predictions for a wide variety of linguistic constructions, for which
learnability has been much debated. Here, we present a new experiment which
tests these learnability predictions. We find that our experimental results
support the possibility that these linguistic constructions are acquired
probabilistically from cognition-general principles.
| 2,010 | Computation and Language |
Complete Complementary Results Report of the MARF's NLP Approach to the
DEFT 2010 Competition | This companion paper complements the main DEFT'10 article describing the MARF
approach (arXiv:0905.1235) to the DEFT'10 NLP challenge (described at
http://www.groupes.polymtl.ca/taln2010/deft.php in French). This paper is aimed
to present the complete result sets of all the conducted experiments and their
settings in the resulting tables highlighting the approach and the best
results, but also showing the worse and the worst and their subsequent
analysis. This particular work focuses on application of the MARF's classical
and NLP pipelines to identification tasks within various francophone corpora to
identify decades when certain articles were published for the first track
(Piste 1) and place of origin of a publication (Piste 2), such as the journal
and location (France vs. Quebec). This is the sixth iteration of the release of
the results.
| 2,014 | Computation and Language |
Testing SDRT's Right Frontier | The Right Frontier Constraint (RFC), as a constraint on the attachment of new
constituents to an existing discourse structure, has important implications for
the interpretation of anaphoric elements in discourse and for Machine Learning
(ML) approaches to learning discourse structures. In this paper we provide
strong empirical support for SDRT's version of RFC. The analysis of about 100
doubly annotated documents by five different naive annotators shows that SDRT's
RFC is respected about 95% of the time. The qualitative analysis of presumed
violations that we have performed shows that they are either click-errors or
structural misconceptions.
| 2,010 | Computation and Language |