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15,202 | Unraveling reported dreams with text analytics | cs.CL | We investigate what distinguishes reported dreams from other personal
narratives. The continuity hypothesis, stemming from psychological dream
analysis work, states that most dreams refer to a person's daily life and
personal concerns, similar to other personal narratives such as diary entries.
Differences between the ... | computer science |
15,203 | From narrative descriptions to MedDRA: automagically encoding adverse
drug reactions | cs.CL | The collection of narrative spontaneous reports is an irreplaceable source
for the prompt detection of suspected adverse drug reactions (ADRs): qualified
domain experts manually revise a huge amount of narrative descriptions and then
encode texts according to MedDRA standard terminology. The manual annotation of
narrat... | computer science |
15,204 | Neural Machine Translation by Minimising the Bayes-risk with Respect to
Syntactic Translation Lattices | cs.CL | We present a novel scheme to combine neural machine translation (NMT) with
traditional statistical machine translation (SMT). Our approach borrows ideas
from linearised lattice minimum Bayes-risk decoding for SMT. The NMT score is
combined with the Bayes-risk of the translation according the SMT lattice. This
makes our... | computer science |
15,205 | Tracking the World State with Recurrent Entity Networks | cs.CL | We introduce a new model, the Recurrent Entity Network (EntNet). It is
equipped with a dynamic long-term memory which allows it to maintain and update
a representation of the state of the world as it receives new data. For
language understanding tasks, it can reason on-the-fly as it reads text, not
just when it is requ... | computer science |
15,206 | ConceptNet 5.5: An Open Multilingual Graph of General Knowledge | cs.CL | Machine learning about language can be improved by supplying it with specific
knowledge and sources of external information. We present here a new version of
the linked open data resource ConceptNet that is particularly well suited to be
used with modern NLP techniques such as word embeddings.
ConceptNet is a knowled... | computer science |
15,207 | Evaluating Automatic Speech Recognition Systems in Comparison With Human
Perception Results Using Distinctive Feature Measures | cs.CL | This paper describes methods for evaluating automatic speech recognition
(ASR) systems in comparison with human perception results, using measures
derived from linguistic distinctive features. Error patterns in terms of
manner, place and voicing are presented, along with an examination of confusion
matrices via a disti... | computer science |
15,208 | Performance Improvements of Probabilistic Transcript-adapted ASR with
Recurrent Neural Network and Language-specific Constraints | cs.CL | Mismatched transcriptions have been proposed as a mean to acquire
probabilistic transcriptions from non-native speakers of a language.Prior work
has demonstrated the value of these transcriptions by successfully adapting
cross-lingual ASR systems for different tar-get languages. In this work, we
describe two techniques... | computer science |
15,209 | Vicinity-Driven Paragraph and Sentence Alignment for Comparable Corpora | cs.CL | Parallel corpora have driven great progress in the field of Text
Simplification. However, most sentence alignment algorithms either offer a
limited range of alignment types supported, or simply ignore valuable clues
present in comparable documents. We address this problem by introducing a new
set of flexible vicinity-d... | computer science |
15,210 | Multi-Perspective Context Matching for Machine Comprehension | cs.CL | Previous machine comprehension (MC) datasets are either too small to train
end-to-end deep learning models, or not difficult enough to evaluate the
ability of current MC techniques. The newly released SQuAD dataset alleviates
these limitations, and gives us a chance to develop more realistic MC models.
Based on this da... | computer science |
15,211 | Building Large Machine Reading-Comprehension Datasets using Paragraph
Vectors | cs.CL | We present a dual contribution to the task of machine reading-comprehension:
a technique for creating large-sized machine-comprehension (MC) datasets using
paragraph-vector models; and a novel, hybrid neural-network architecture that
combines the representation power of recurrent neural networks with the
discriminative... | computer science |
15,212 | Hypernyms under Siege: Linguistically-motivated Artillery for Hypernymy
Detection | cs.CL | The fundamental role of hypernymy in NLP has motivated the development of
many methods for the automatic identification of this relation, most of which
rely on word distribution. We investigate an extensive number of such
unsupervised measures, using several distributional semantic models that differ
by context type an... | computer science |
15,213 | Mining Compatible/Incompatible Entities from Question and Answering via
Yes/No Answer Classification using Distant Label Expansion | cs.CL | Product Community Question Answering (PCQA) provides useful information about
products and their features (aspects) that may not be well addressed by product
descriptions and reviews. We observe that a product's compatibility issues with
other products are frequently discussed in PCQA and such issues are more
frequentl... | computer science |
15,214 | Grammatical Constraints on Intra-sentential Code-Switching: From
Theories to Working Models | cs.CL | We make one of the first attempts to build working models for
intra-sentential code-switching based on the Equivalence-Constraint (Poplack
1980) and Matrix-Language (Myers-Scotton 1993) theories. We conduct a detailed
theoretical analysis, and a small-scale empirical study of the two models for
Hindi-English CS. Our an... | computer science |
15,215 | Neural Emoji Recommendation in Dialogue Systems | cs.CL | Emoji is an essential component in dialogues which has been broadly utilized
on almost all social platforms. It could express more delicate feelings beyond
plain texts and thus smooth the communications between users, making dialogue
systems more anthropomorphic and vivid. In this paper, we focus on
automatically recom... | computer science |
15,216 | How Grammatical is Character-level Neural Machine Translation? Assessing
MT Quality with Contrastive Translation Pairs | cs.CL | Analysing translation quality in regards to specific linguistic phenomena has
historically been difficult and time-consuming. Neural machine translation has
the attractive property that it can produce scores for arbitrary translations,
and we propose a novel method to assess how well NMT systems model specific
linguist... | computer science |
15,217 | Unsupervised Clustering of Commercial Domains for Adaptive Machine
Translation | cs.CL | In this paper, we report on domain clustering in the ambit of an adaptive MT
architecture. A standard bottom-up hierarchical clustering algorithm has been
instantiated with five different distances, which have been compared, on an MT
benchmark built on 40 commercial domains, in terms of dendrograms, intrinsic
and extri... | computer science |
15,218 | Multilingual Word Embeddings using Multigraphs | cs.CL | We present a family of neural-network--inspired models for computing
continuous word representations, specifically designed to exploit both
monolingual and multilingual text. This framework allows us to perform
unsupervised training of embeddings that exhibit higher accuracy on syntactic
and semantic compositionality, ... | computer science |
15,219 | CoPaSul Manual - Contour-based parametric and superpositional intonation
stylization | cs.CL | The purposes of the CoPaSul toolkit are (1) automatic prosodic annotation and
(2) prosodic feature extraction from syllable to utterance level. CoPaSul
stands for contour-based, parametric, superpositional intonation stylization.
In this framework intonation is represented as a superposition of global and
local contour... | computer science |
15,220 | Transition-based Parsing with Context Enhancement and Future Reward
Reranking | cs.CL | This paper presents a novel reranking model, future reward reranking, to
re-score the actions in a transition-based parser by using a global scorer.
Different to conventional reranking parsing, the model searches for the best
dependency tree in all feasible trees constraining by a sequence of actions to
get the future ... | computer science |
15,221 | Building a robust sentiment lexicon with (almost) no resource | cs.CL | Creating sentiment polarity lexicons is labor intensive. Automatically
translating them from resourceful languages requires in-domain machine
translation systems, which rely on large quantities of bi-texts. In this paper,
we propose to replace machine translation by transferring words from the
lexicon through word embe... | computer science |
15,222 | Modeling Trolling in Social Media Conversations | cs.CL | Social media websites, electronic newspapers and Internet forums allow
visitors to leave comments for others to read and interact. This exchange is
not free from participants with malicious intentions, who troll others by
positing messages that are intended to be provocative, offensive, or menacing.
With the goal of fa... | computer science |
15,223 | Automatic Labelling of Topics with Neural Embeddings | cs.CL | Topics generated by topic models are typically represented as list of terms.
To reduce the cognitive overhead of interpreting these topics for end-users, we
propose labelling a topic with a succinct phrase that summarises its theme or
idea. Using Wikipedia document titles as label candidates, we compute neural
embeddin... | computer science |
15,224 | A Two-Phase Approach Towards Identifying Argument Structure in Natural
Language | cs.CL | We propose a new approach for extracting argument structure from natural
language texts that contain an underlying argument. Our approach comprises of
two phases: Score Assignment and Structure Prediction. The Score Assignment
phase trains models to classify relations between argument units (Support,
Attack or Neutral)... | computer science |
15,225 | Neural Networks Classifier for Data Selection in Statistical Machine
Translation | cs.CL | We address the data selection problem in statistical machine translation
(SMT) as a classification task. The new data selection method is based on a
neural network classifier. We present a new method description and empirical
results proving that our data selection method provides better translation
quality, compared t... | computer science |
15,226 | Neural Multi-Source Morphological Reinflection | cs.CL | We explore the task of multi-source morphological reinflection, which
generalizes the standard, single-source version. The input consists of (i) a
target tag and (ii) multiple pairs of source form and source tag for a lemma.
The motivation is that it is beneficial to have access to more than one source
form since diffe... | computer science |
15,227 | Boosting Neural Machine Translation | cs.CL | Training efficiency is one of the main problems for Neural Machine
Translation (NMT). Deep networks need for very large data as well as many
training iterations to achieve state-of-the-art performance. This results in
very high computation cost, slowing down research and industrialisation. In
this paper, we propose to ... | computer science |
15,228 | Neural Machine Translation from Simplified Translations | cs.CL | Text simplification aims at reducing the lexical, grammatical and structural
complexity of a text while keeping the same meaning. In the context of machine
translation, we introduce the idea of simplified translations in order to boost
the learning ability of deep neural translation models. We conduct preliminary
exper... | computer science |
15,229 | Domain Control for Neural Machine Translation | cs.CL | Machine translation systems are very sensitive to the domains they were
trained on. Several domain adaptation techniques have been deeply studied. We
propose a new technique for neural machine translation (NMT) that we call
domain control which is performed at runtime using a unique neural network
covering multiple dom... | computer science |
15,230 | Domain specialization: a post-training domain adaptation for Neural
Machine Translation | cs.CL | Domain adaptation is a key feature in Machine Translation. It generally
encompasses terminology, domain and style adaptation, especially for human
post-editing workflows in Computer Assisted Translation (CAT). With Neural
Machine Translation (NMT), we introduce a new notion of domain adaptation that
we call "specializa... | computer science |
15,231 | Span-Based Constituency Parsing with a Structure-Label System and
Provably Optimal Dynamic Oracles | cs.CL | Parsing accuracy using efficient greedy transition systems has improved
dramatically in recent years thanks to neural networks. Despite striking
results in dependency parsing, however, neural models have not surpassed
state-of-the-art approaches in constituency parsing. To remedy this, we
introduce a new shift-reduce s... | computer science |
15,232 | Exploring Different Dimensions of Attention for Uncertainty Detection | cs.CL | Neural networks with attention have proven effective for many natural
language processing tasks. In this paper, we develop attention mechanisms for
uncertainty detection. In particular, we generalize standardly used attention
mechanisms by introducing external attention and sequence-preserving attention.
These novel ar... | computer science |
15,233 | Unsupervised Dialogue Act Induction using Gaussian Mixtures | cs.CL | This paper introduces a new unsupervised approach for dialogue act induction.
Given the sequence of dialogue utterances, the task is to assign them the
labels representing their function in the dialogue.
Utterances are represented as real-valued vectors encoding their meaning. We
model the dialogue as Hidden Markov m... | computer science |
15,234 | Grammar rules for the isiZulu complex verb | cs.CL | The isiZulu verb is known for its morphological complexity, which is a
subject for on-going linguistics research, as well as for prospects of
computational use, such as controlled natural language interfaces, machine
translation, and spellcheckers. To this end, we seek to answer the question as
to what the precise gram... | computer science |
15,235 | Inferring the location of authors from words in their texts | cs.CL | For the purposes of computational dialectology or other geographically bound
text analysis tasks, texts must be annotated with their or their authors'
location. Many texts are locatable through explicit labels but most have no
explicit annotation of place. This paper describes a series of experiments to
determine how p... | computer science |
15,236 | Stateology: State-Level Interactive Charting of Language, Feelings, and
Values | cs.CL | People's personality and motivations are manifest in their everyday language
usage. With the emergence of social media, ample examples of such usage are
procurable. In this paper, we aim to analyze the vocabulary used by close to
200,000 Blogger users in the U.S. with the purpose of geographically portraying
various de... | computer science |
15,237 | SCDV : Sparse Composite Document Vectors using soft clustering over
distributional representations | cs.CL | We present a feature vector formation technique for documents - Sparse
Composite Document Vector (SCDV) - which overcomes several shortcomings of the
current distributional paragraph vector representations that are widely used
for text representation. In SCDV, word embedding's are clustered to capture
multiple semantic... | computer science |
15,238 | User Bias Removal in Review Score Prediction | cs.CL | Review score prediction of text reviews has recently gained a lot of
attention in recommendation systems. A major problem in models for review score
prediction is the presence of noise due to user-bias in review scores. We
propose two simple statistical methods to remove such noise and improve review
score prediction. ... | computer science |
15,239 | Fast Domain Adaptation for Neural Machine Translation | cs.CL | Neural Machine Translation (NMT) is a new approach for automatic translation
of text from one human language into another. The basic concept in NMT is to
train a large Neural Network that maximizes the translation performance on a
given parallel corpus. NMT is gaining popularity in the research community
because it out... | computer science |
15,240 | Sparse Coding of Neural Word Embeddings for Multilingual Sequence
Labeling | cs.CL | In this paper we propose and carefully evaluate a sequence labeling framework
which solely utilizes sparse indicator features derived from dense distributed
word representations. The proposed model obtains (near) state-of-the art
performance for both part-of-speech tagging and named entity recognition for a
variety of ... | computer science |
15,241 | Inverted Bilingual Topic Models for Lexicon Extraction from Non-parallel
Data | cs.CL | Topic models have been successfully applied in lexicon extraction. However,
most previous methods are limited to document-aligned data. In this paper, we
try to address two challenges of applying topic models to lexicon extraction in
non-parallel data: 1) hard to model the word relationship and 2) noisy seed
dictionary... | computer science |
15,242 | Continuous multilinguality with language vectors | cs.CL | Most existing models for multilingual natural language processing (NLP) treat
language as a discrete category, and make predictions for either one language
or the other. In contrast, we propose using continuous vector representations
of language. We show that these can be learned efficiently with a
character-based neur... | computer science |
15,243 | Noise Mitigation for Neural Entity Typing and Relation Extraction | cs.CL | In this paper, we address two different types of noise in information
extraction models: noise from distant supervision and noise from pipeline input
features. Our target tasks are entity typing and relation extraction. For the
first noise type, we introduce multi-instance multi-label learning algorithms
using neural n... | computer science |
15,244 | A CRF Based POS Tagger for Code-mixed Indian Social Media Text | cs.CL | In this work, we describe a conditional random fields (CRF) based system for
Part-Of- Speech (POS) tagging of code-mixed Indian social media text as part of
our participation in the tool contest on POS tagging for codemixed Indian
social media text, held in conjunction with the 2016 International Conference
on Natural ... | computer science |
15,245 | Language Modeling with Gated Convolutional Networks | cs.CL | The pre-dominant approach to language modeling to date is based on recurrent
neural networks. Their success on this task is often linked to their ability to
capture unbounded context. In this paper we develop a finite context approach
through stacked convolutions, which can be more efficient since they allow
paralleliz... | computer science |
15,246 | KS_JU@DPIL-FIRE2016:Detecting Paraphrases in Indian Languages Using
Multinomial Logistic Regression Model | cs.CL | In this work, we describe a system that detects paraphrases in Indian
Languages as part of our participation in the shared Task on detecting
paraphrases in Indian Languages (DPIL) organized by Forum for Information
Retrieval Evaluation (FIRE) in 2016. Our paraphrase detection method uses a
multinomial logistic regressi... | computer science |
15,247 | Understanding Neural Networks through Representation Erasure | cs.CL | While neural networks have been successfully applied to many natural language
processing tasks, they come at the cost of interpretability. In this paper, we
propose a general methodology to analyze and interpret decisions from a neural
model by observing the effects on the model of erasing various parts of the
represen... | computer science |
15,248 | Text Summarization using Deep Learning and Ridge Regression | cs.CL | We develop models and extract relevant features for automatic text
summarization and investigate the performance of different models on the DUC
2001 dataset. Two different models were developed, one being a ridge regressor
and the other one was a multi-layer perceptron. The hyperparameters were varied
and their perform... | computer science |
15,249 | Abstractive Headline Generation for Spoken Content by Attentive
Recurrent Neural Networks with ASR Error Modeling | cs.CL | Headline generation for spoken content is important since spoken content is
difficult to be shown on the screen and browsed by the user. It is a special
type of abstractive summarization, for which the summaries are generated word
by word from scratch without using any part of the original content. Many deep
learning a... | computer science |
15,250 | Shamela: A Large-Scale Historical Arabic Corpus | cs.CL | Arabic is a widely-spoken language with a rich and long history spanning more
than fourteen centuries. Yet existing Arabic corpora largely focus on the
modern period or lack sufficient diachronic information. We develop a
large-scale, historical corpus of Arabic of about 1 billion words from diverse
periods of time. We... | computer science |
15,251 | Here's My Point: Joint Pointer Architecture for Argument Mining | cs.CL | One of the major goals in automated argumentation mining is to uncover the
argument structure present in argumentative text. In order to determine this
structure, one must understand how different individual components of the
overall argument are linked. General consensus in this field dictates that the
argument compon... | computer science |
15,252 | Deep Semi-Supervised Learning with Linguistically Motivated Sequence
Labeling Task Hierarchies | cs.CL | In this paper we present a novel Neural Network algorithm for conducting
semi-supervised learning for sequence labeling tasks arranged in a
linguistically motivated hierarchy. This relationship is exploited to
regularise the representations of supervised tasks by backpropagating the error
of the unsupervised task throu... | computer science |
15,253 | Network statistics on early English Syntax: Structural criteria | cs.CL | 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 ou... | computer science |
15,254 | Discriminative Phoneme Sequences Extraction for Non-Native Speaker's
Origin Classification | cs.CL | 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... | computer science |
15,255 | Combined Acoustic and Pronunciation Modelling for Non-Native Speech
Recognition | cs.CL | 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 ... | computer science |
15,256 | Amélioration des Performances des Systèmes Automatiques de
Reconnaissance de la Parole pour la Parole Non Native | cs.CL | 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 tar... | computer science |
15,257 | Proof nets for display logic | cs.CL | 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 explora... | computer science |
15,258 | Morphological annotation of Korean with Directly Maintainable Resources | cs.CL | 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 morp... | computer science |
15,259 | Lexicon management and standard formats | cs.CL | 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 p... | computer science |
15,260 | In memoriam Maurice Gross | cs.CL | 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 | computer science |
15,261 | A resource-based Korean morphological annotation system | cs.CL | 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 th... | computer science |
15,262 | Graphes paramétrés et outils de lexicalisation | cs.CL | 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 gram... | computer science |
15,263 | Evaluation of a Grammar of French Determiners | cs.CL | 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 transiti... | computer science |
15,264 | Very strict selectional restrictions | cs.CL | 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:... | computer science |
15,265 | Outilex, plate-forme logicielle de traitement de textes écrits | cs.CL | 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 structur... | computer science |
15,266 | Let's get the student into the driver's seat | cs.CL | 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 acqu... | computer science |
15,267 | Valence extraction using EM selection and co-occurrence matrices | cs.CL | 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 pos... | computer science |
15,268 | Why has (reasonably accurate) Automatic Speech Recognition been so hard
to achieve? | cs.CL | 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 re... | computer science |
15,269 | Change of word types to word tokens ratio in the course of translation
(based on Russian translations of K. Vonnegut novels) | cs.CL | 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-Rus... | computer science |
15,270 | Linguistic Geometries for Unsupervised Dimensionality Reduction | cs.CL | 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 b... | computer science |
15,271 | Automatic derivation of domain terms and concept location based on the
analysis of the identifiers | cs.CL | 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 vocabul... | computer science |
15,272 | A Computational Algorithm based on Empirical Analysis, that Composes
Sanskrit Poetry | cs.CL | 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 pros... | computer science |
15,273 | Les Entités Nommées : usage et degrés de précision et de
désambiguïsation | cs.CL | 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... | computer science |
15,274 | La représentation formelle des concepts spatiaux dans la langue | cs.CL | 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 the... | computer science |
15,275 | Les entités spatiales dans la langue : étude descriptive, formelle
et expérimentale de la catégorisation | cs.CL | 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 dynam... | computer science |
15,276 | Learning Recursive Segments for Discourse Parsing | cs.CL | 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 a... | computer science |
15,277 | Symmetric categorial grammar: residuation and Galois connections | cs.CL | The Lambek-Grishin calculus is a symmetric extension of the Lambek calculus:
in addition to the residuated family of product, left and right division
operations of Lambek's original calculus, one also considers a family of
coproduct, right and left difference operations, related to the former by an
arrow-reversing dual... | computer science |
15,278 | For the sake of simplicity: Unsupervised extraction of lexical
simplifications from Wikipedia | cs.CL | We report on work in progress on extracting lexical simplifications (e.g.,
"collaborate" -> "work together"), focusing on utilizing edit histories in
Simple English Wikipedia for this task. We consider two main approaches: (1)
deriving simplification probabilities via an edit model that accounts for a
mixture of differ... | computer science |
15,279 | Don't 'have a clue'? Unsupervised co-learning of downward-entailing
operators | cs.CL | Researchers in textual entailment have begun to consider inferences involving
'downward-entailing operators', an interesting and important class of lexical
items that change the way inferences are made. Recent work proposed a method
for learning English downward-entailing operators that requires access to a
high-qualit... | computer science |
15,280 | Statistical Sign Language Machine Translation: from English written text
to American Sign Language Gloss | cs.CL | This works aims to design a statistical machine translation from English text
to American Sign Language (ASL). The system is based on Moses tool with some
modifications and the results are synthesized through a 3D avatar for
interpretation. First, we translate the input text to gloss, a written form of
ASL. Second, we ... | computer science |
15,281 | Grammatical Relations of Myanmar Sentences Augmented by
Transformation-Based Learning of Function Tagging | cs.CL | In this paper we describe function tagging using Transformation Based
Learning (TBL) for Myanmar that is a method of extensions to the previous
statistics-based function tagger. Contextual and lexical rules (developed using
TBL) were critical in achieving good results. First, we describe a method for
expressing lexical... | computer science |
15,282 | Creating a Live, Public Short Message Service Corpus: The NUS SMS Corpus | cs.CL | Short Message Service (SMS) messages are largely sent directly from one
person to another from their mobile phones. They represent a means of personal
communication that is an important communicative artifact in our current
digital era. As most existing studies have used private access to SMS corpora,
comparative studi... | computer science |
15,283 | Visualization and Analysis of Frames in Collections of Messages: Content
Analysis and the Measurement of Meaning | cs.CL | A step-to-step introduction is provided on how to generate a semantic map
from a collection of messages (full texts, paragraphs or statements) using
freely available software and/or SPSS for the relevant statistics and the
visualization. The techniques are discussed in the various theoretical contexts
of (i) linguistic... | computer science |
15,284 | Proof nets for the Lambek-Grishin calculus | cs.CL | Grishin's generalization of Lambek's Syntactic Calculus combines a
non-commutative multiplicative conjunction and its residuals (product, left and
right division) with a dual family: multiplicative disjunction, right and left
difference. Interaction between these two families takes the form of linear
distributivity pri... | computer science |
15,285 | Transition-Based Dependency Parsing With Pluggable Classifiers | cs.CL | In principle, the design of transition-based dependency parsers makes it
possible to experiment with any general-purpose classifier without other
changes to the parsing algorithm. In practice, however, it often takes
substantial software engineering to bridge between the different
representations used by two software p... | computer science |
15,286 | Detecting English Writing Styles For Non-native Speakers | cs.CL | Analyzing writing styles of non-native speakers is a challenging task. In
this paper, we analyze the comments written in the discussion pages of the
English Wikipedia. Using learning algorithms, we are able to detect native
speakers' writing style with an accuracy of 74%. Given the diversity of the
English Wikipedia us... | computer science |
15,287 | A Principled Approach to Grammars for Controlled Natural Languages and
Predictive Editors | cs.CL | Controlled natural languages (CNL) with a direct mapping to formal logic have
been proposed to improve the usability of knowledge representation systems,
query interfaces, and formal specifications. Predictive editors are a popular
approach to solve the problem that CNLs are easy to read but hard to write.
Such predict... | computer science |
15,288 | Semantic Polarity of Adjectival Predicates in Online Reviews | cs.CL | Web users produce more and more documents expressing opinions. Because these
have become important resources for customers and manufacturers, many have
focused on them. Opinions are often expressed through adjectives with positive
or negative semantic values. In extracting information from users' opinion in
online revi... | computer science |
15,289 | Improving Pointwise Mutual Information (PMI) by Incorporating
Significant Co-occurrence | cs.CL | We design a new co-occurrence based word association measure by incorporating
the concept of significant cooccurrence in the popular word association measure
Pointwise Mutual Information (PMI). By extensive experiments with a large
number of publicly available datasets we show that the newly introduced measure
performs... | computer science |
15,290 | Intelligent Hybrid Man-Machine Translation Quality Estimation | cs.CL | Inferring evaluation scores based on human judgments is invaluable compared
to using current evaluation metrics which are not suitable for real-time
applications e.g. post-editing. However, these judgments are much more
expensive to collect especially from expert translators, compared to evaluation
based on indicators ... | computer science |
15,291 | Improving the quality of Gujarati-Hindi Machine Translation through
part-of-speech tagging and stemmer-assisted transliteration | cs.CL | Machine Translation for Indian languages is an emerging research area.
Transliteration is one such module that we design while designing a translation
system. Transliteration means mapping of source language text into the target
language. Simple mapping decreases the efficiency of overall translation
system. We propose... | computer science |
15,292 | Part of Speech Tagging of Marathi Text Using Trigram Method | cs.CL | In this paper we present a Marathi part of speech tagger. It is a
morphologically rich language. It is spoken by the native people of
Maharashtra. The general approach used for development of tagger is statistical
using trigram Method. The main concept of trigram is to explore the most likely
POS for a token based on g... | computer science |
15,293 | Rule Based Transliteration Scheme for English to Punjabi | cs.CL | Machine Transliteration has come out to be an emerging and a very important
research area in the field of machine translation. Transliteration basically
aims to preserve the phonological structure of words. Proper transliteration of
name entities plays a very significant role in improving the quality of machine
transla... | computer science |
15,294 | Clustering Algorithm for Gujarati Language | cs.CL | Natural language processing area is still under research. But now a day it is
on platform for worldwide researchers. Natural language processing includes
analyzing the language based on its structure and then tagging of each word
appropriately with its grammar base. Here we have 50,000 tagged words set and
we try to cl... | computer science |
15,295 | Human and Automatic Evaluation of English-Hindi Machine Translation | cs.CL | For the past 60 years, Research in machine translation is going on. For the
development in this field, a lot of new techniques are being developed each
day. As a result, we have witnessed development of many automatic machine
translators. A manager of machine translation development project needs to know
the performanc... | computer science |
15,296 | Learning Frames from Text with an Unsupervised Latent Variable Model | cs.CL | We develop a probabilistic latent-variable model to discover semantic
frames---types of events and their participants---from corpora. We present a
Dirichlet-multinomial model in which frames are latent categories that explain
the linking of verb-subject-object triples, given document-level sparsity. We
analyze what the... | computer science |
15,297 | Improving the Quality of MT Output using Novel Name Entity Translation
Scheme | cs.CL | This paper presents a novel approach to machine translation by combining the
state of art name entity translation scheme. Improper translation of name
entities lapse the quality of machine translated output. In this work, name
entities are transliterated by using statistical rule based approach. This
paper describes th... | computer science |
15,298 | Development of Marathi Part of Speech Tagger Using Statistical Approach | cs.CL | Part-of-speech (POS) tagging is a process of assigning the words in a text
corresponding to a particular part of speech. A fundamental version of POS
tagging is the identification of words as nouns, verbs, adjectives etc. For
processing natural languages, Part of Speech tagging is a prominent tool. It is
one of the sim... | computer science |
15,299 | Subjective and Objective Evaluation of English to Urdu Machine
Translation | cs.CL | Machine translation is research based area where evaluation is very important
phenomenon for checking the quality of MT output. The work is based on the
evaluation of English to Urdu Machine translation. In this research work we
have evaluated the translation quality of Urdu language which has been
translated by using ... | computer science |
15,300 | Rule Based Stemmer in Urdu | cs.CL | Urdu is a combination of several languages like Arabic, Hindi, English,
Turkish, Sanskrit etc. It has a complex and rich morphology. This is the reason
why not much work has been done in Urdu language processing. Stemming is used
to convert a word into its respective root form. In stemming, we separate the
suffix and p... | computer science |
15,301 | Stemmers for Tamil Language: Performance Analysis | cs.CL | Stemming is the process of extracting root word from the given inflection
word and also plays significant role in numerous application of Natural
Language Processing (NLP). Tamil Language raises several challenges to NLP,
since it has rich morphological patterns than other languages. The rule based
approach light-stemm... | computer science |
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