Unnamed: 0 int64 0 41k | title stringlengths 4 274 | category stringlengths 5 18 | summary stringlengths 22 3.66k | theme stringclasses 8
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15,502 | Discriminative Segmental Cascades for Feature-Rich Phone Recognition | cs.CL | Discriminative segmental models, such as segmental conditional random fields
(SCRFs) and segmental structured support vector machines (SSVMs), have had
success in speech recognition via both lattice rescoring and first-pass
decoding. However, such models suffer from slow decoding, hampering the use of
computationally e... | computer science |
15,503 | Reasoning about Linguistic Regularities in Word Embeddings using Matrix
Manifolds | cs.CL | Recent work has explored methods for learning continuous vector space word
representations reflecting the underlying semantics of words. Simple vector
space arithmetic using cosine distances has been shown to capture certain types
of analogies, such as reasoning about plurals from singulars, past tense from
present ten... | computer science |
15,504 | Classifying informative and imaginative prose using complex networks | cs.CL | Statistical methods have been widely employed in recent years to grasp many
language properties. The application of such techniques have allowed an
improvement of several linguistic applications, which encompasses machine
translation, automatic summarization and document classification. In the
latter, many approaches h... | computer science |
15,505 | One model, two languages: training bilingual parsers with harmonized
treebanks | cs.CL | We introduce an approach to train lexicalized parsers using bilingual corpora
obtained by merging harmonized treebanks of different languages, producing
parsers that can analyze sentences in either of the learned languages, or even
sentences that mix both. We test the approach on the Universal Dependency
Treebanks, tra... | computer science |
15,506 | Unsupervised Sentence Simplification Using Deep Semantics | cs.CL | We present a novel approach to sentence simplification which departs from
previous work in two main ways. First, it requires neither hand written rules
nor a training corpus of aligned standard and simplified sentences. Second,
sentence splitting operates on deep semantic structure. We show (i) that the
unsupervised fr... | computer science |
15,507 | Multilayer Network of Language: a Unified Framework for Structural
Analysis of Linguistic Subsystems | cs.CL | Recently, the focus of complex networks research has shifted from the
analysis of isolated properties of a system toward a more realistic modeling of
multiple phenomena - multilayer networks. Motivated by the prosperity of
multilayer approach in social, transport or trade systems, we propose the
introduction of multila... | computer science |
15,508 | Separated by an Un-common Language: Towards Judgment Language Informed
Vector Space Modeling | cs.CL | A common evaluation practice in the vector space models (VSMs) literature is
to measure the models' ability to predict human judgments about lexical
semantic relations between word pairs. Most existing evaluation sets, however,
consist of scores collected for English word pairs only, ignoring the potential
impact of th... | computer science |
15,509 | Compositional Semantic Parsing on Semi-Structured Tables | cs.CL | Two important aspects of semantic parsing for question answering are the
breadth of the knowledge source and the depth of logical compositionality.
While existing work trades off one aspect for another, this paper
simultaneously makes progress on both fronts through a new task: answering
complex questions on semi-struc... | computer science |
15,510 | Improved Transition-Based Parsing by Modeling Characters instead of
Words with LSTMs | cs.CL | We present extensions to a continuous-state dependency parsing method that
makes it applicable to morphologically rich languages. Starting with a
high-performance transition-based parser that uses long short-term memory
(LSTM) recurrent neural networks to learn representations of the parser state,
we replace lookup-bas... | computer science |
15,511 | Word sense disambiguation: a survey | cs.CL | In this paper, we made a survey on Word Sense Disambiguation (WSD). Near
about in all major languages around the world, research in WSD has been
conducted upto different extents. In this paper, we have gone through a survey
regarding the different approaches adopted in different research works, the
State of the Art in ... | computer science |
15,512 | Automatic classification of bengali sentences based on sense definitions
present in bengali wordnet | cs.CL | Based on the sense definition of words available in the Bengali WordNet, an
attempt is made to classify the Bengali sentences automatically into different
groups in accordance with their underlying senses. The input sentences are
collected from 50 different categories of the Bengali text corpus developed in
the TDIL pr... | computer science |
15,513 | Hyponymy extraction of domain ontology concept based on ccrfs and
hierarchy clustering | cs.CL | Concept hierarchy is the backbone of ontology, and the concept hierarchy
acquisition has been a hot topic in the field of ontology learning. this paper
proposes a hyponymy extraction method of domain ontology concept based on
cascaded conditional random field(CCRFs) and hierarchy clustering. It takes
free text as extra... | computer science |
15,514 | Study of Phonemes Confusions in Hierarchical Automatic Phoneme
Recognition System | cs.CL | In this paper, we have analyzed the impact of confusions on the robustness of
phoneme recognitions system. The confusions are detected at the pronunciation
and the confusions matrices of the phoneme recognizer. The confusions show that
some similarities between phonemes at the pronunciation affect significantly
the rec... | computer science |
15,515 | Semantically Conditioned LSTM-based Natural Language Generation for
Spoken Dialogue Systems | cs.CL | Natural language generation (NLG) is a critical component of spoken dialogue
and it has a significant impact both on usability and perceived quality. Most
NLG systems in common use employ rules and heuristics and tend to generate
rigid and stylised responses without the natural variation of human language.
They are als... | computer science |
15,516 | Stochastic Language Generation in Dialogue using Recurrent Neural
Networks with Convolutional Sentence Reranking | cs.CL | The natural language generation (NLG) component of a spoken dialogue system
(SDS) usually needs a substantial amount of handcrafting or a well-labeled
dataset to be trained on. These limitations add significantly to development
costs and make cross-domain, multi-lingual dialogue systems intractable.
Moreover, human lan... | computer science |
15,517 | Bidirectional LSTM-CRF Models for Sequence Tagging | cs.CL | In this paper, we propose a variety of Long Short-Term Memory (LSTM) based
models for sequence tagging. These models include LSTM networks, bidirectional
LSTM (BI-LSTM) networks, LSTM with a Conditional Random Field (CRF) layer
(LSTM-CRF) and bidirectional LSTM with a CRF layer (BI-LSTM-CRF). Our work is
the first to a... | computer science |
15,518 | An Automatic Machine Translation Evaluation Metric Based on Dependency
Parsing Model | cs.CL | Most of the syntax-based metrics obtain the similarity by comparing the
sub-structures extracted from the trees of hypothesis and reference. These
sub-structures are defined by human and can't express all the information in
the trees because of the limited length of sub-structures. In addition, the
overlapped parts bet... | computer science |
15,519 | Egyptian Dialect Stopword List Generation from Social Network Data | cs.CL | This paper proposes a methodology for generating a stopword list from online
social network (OSN) corpora in Egyptian Dialect(ED). The aim of the paper is
to investigate the effect of removingED stopwords on the Sentiment Analysis
(SA) task. The stopwords lists generated before were on Modern Standard Arabic
(MSA) whic... | computer science |
15,520 | Finding Function in Form: Compositional Character Models for Open
Vocabulary Word Representation | cs.CL | We introduce a model for constructing vector representations of words by
composing characters using bidirectional LSTMs. Relative to traditional word
representation models that have independent vectors for each word type, our
model requires only a single vector per character type and a fixed set of
parameters for the c... | computer science |
15,521 | Feature-based Decipherment for Large Vocabulary Machine Translation | cs.CL | Orthographic similarities across languages provide a strong signal for
probabilistic decipherment, especially for closely related language pairs. The
existing decipherment models, however, are not well-suited for exploiting these
orthographic similarities. We propose a log-linear model with latent variables
that incorp... | computer science |
15,522 | Improve the Evaluation of Fluency Using Entropy for Machine Translation
Evaluation Metrics | cs.CL | The widely-used automatic evaluation metrics cannot adequately reflect the
fluency of the translations. The n-gram-based metrics, like BLEU, limit the
maximum length of matched fragments to n and cannot catch the matched fragments
longer than n, so they can only reflect the fluency indirectly. METEOR, which
is not limi... | computer science |
15,523 | Adapting Phrase-based Machine Translation to Normalise Medical Terms in
Social Media Messages | cs.CL | Previous studies have shown that health reports in social media, such as
DailyStrength and Twitter, have potential for monitoring health conditions
(e.g. adverse drug reactions, infectious diseases) in particular communities.
However, in order for a machine to understand and make inferences on these
health conditions, ... | computer science |
15,524 | Measuring Word Significance using Distributed Representations of Words | cs.CL | Distributed representations of words as real-valued vectors in a relatively
low-dimensional space aim at extracting syntactic and semantic features from
large text corpora. A recently introduced neural network, named word2vec
(Mikolov et al., 2013a; Mikolov et al., 2013b), was shown to encode semantic
information in th... | computer science |
15,525 | Removing Biases from Trainable MT Metrics by Using Self-Training | cs.CL | Most trainable machine translation (MT) metrics train their weights on human
judgments of state-of-the-art MT systems outputs. This makes trainable metrics
biases in many ways. One of them is preferring longer translations. These
biased metrics when used for tuning are evaluating different types of
translations -- n-be... | computer science |
15,526 | Syntax Evolution: Problems and Recursion | cs.CL | Why did only we humans evolve Turing completeness? Turing completeness is the
maximum computing power, and we are Turing complete because we can calculate
whatever any Turing machine can compute. Thus we can learn any natural or
artificial language, and it seems that no other species can, so we are the only
Turing comp... | computer science |
15,527 | Effective Approaches to Attention-based Neural Machine Translation | cs.CL | An attentional mechanism has lately been used to improve neural machine
translation (NMT) by selectively focusing on parts of the source sentence
during translation. However, there has been little work exploring useful
architectures for attention-based NMT. This paper examines two simple and
effective classes of attent... | computer science |
15,528 | Learning Meta-Embeddings by Using Ensembles of Embedding Sets | cs.CL | Word embeddings -- distributed representations of words -- in deep learning
are beneficial for many tasks in natural language processing (NLP). However,
different embedding sets vary greatly in quality and characteristics of the
captured semantics. Instead of relying on a more advanced algorithm for
embedding learning,... | computer science |
15,529 | Probabilistic Modelling of Morphologically Rich Languages | cs.CL | This thesis investigates how the sub-structure of words can be accounted for
in probabilistic models of language. Such models play an important role in
natural language processing tasks such as translation or speech recognition,
but often rely on the simplistic assumption that words are opaque symbols. This
assumption ... | computer science |
15,530 | Exploring Metaphorical Senses and Word Representations for Identifying
Metonyms | cs.CL | A metonym is a word with a figurative meaning, similar to a metaphor. Because
metonyms are closely related to metaphors, we apply features that are used
successfully for metaphor recognition to the task of detecting metonyms. On the
ACL SemEval 2007 Task 8 data with gold standard metonym annotations, our system
achieve... | computer science |
15,531 | Auto-Sizing Neural Networks: With Applications to n-gram Language Models | cs.CL | Neural networks have been shown to improve performance across a range of
natural-language tasks. However, designing and training them can be
complicated. Frequently, researchers resort to repeated experimentation to pick
optimal settings. In this paper, we address the issue of choosing the correct
number of units in hi... | computer science |
15,532 | Posterior calibration and exploratory analysis for natural language
processing models | cs.CL | Many models in natural language processing define probabilistic distributions
over linguistic structures. We argue that (1) the quality of a model' s
posterior distribution can and should be directly evaluated, as to whether
probabilities correspond to empirical frequencies, and (2) NLP uncertainty can
be projected not... | computer science |
15,533 | A large annotated corpus for learning natural language inference | cs.CL | Understanding entailment and contradiction is fundamental to understanding
natural language, and inference about entailment and contradiction is a
valuable testing ground for the development of semantic representations.
However, machine learning research in this area has been dramatically limited
by the lack of large-s... | computer science |
15,534 | Visualizing NLP annotations for Crowdsourcing | cs.CL | Visualizing NLP annotation is useful for the collection of training data for
the statistical NLP approaches. Existing toolkits either provide limited visual
aid, or introduce comprehensive operators to realize sophisticated linguistic
rules. Workers must be well trained to use them. Their audience thus can hardly
be sc... | computer science |
15,535 | Alignment-based compositional semantics for instruction following | cs.CL | This paper describes an alignment-based model for interpreting natural
language instructions in context. We approach instruction following as a search
over plans, scoring sequences of actions conditioned on structured observations
of text and the environment. By explicitly modeling both the low-level
compositional stru... | computer science |
15,536 | Component-Enhanced Chinese Character Embeddings | cs.CL | Distributed word representations are very useful for capturing semantic
information and have been successfully applied in a variety of NLP tasks,
especially on English. In this work, we innovatively develop two
component-enhanced Chinese character embedding models and their bigram
extensions. Distinguished from English... | computer science |
15,537 | Computational Sociolinguistics: A Survey | cs.CL | Language is a social phenomenon and variation is inherent to its social
nature. Recently, there has been a surge of interest within the computational
linguistics (CL) community in the social dimension of language. In this article
we present a survey of the emerging field of "Computational Sociolinguistics"
that reflect... | computer science |
15,538 | An Event Network for Exploring Open Information | cs.CL | In this paper, an event network is presented for exploring open information,
where linguistic units about an event are organized for analysing. The process
is divided into three steps: document event detection, event network
construction and event network analysis. First, by implementing event detection
or tracking, do... | computer science |
15,539 | Neural Machine Translation of Rare Words with Subword Units | cs.CL | Neural machine translation (NMT) models typically operate with a fixed
vocabulary, but translation is an open-vocabulary problem. Previous work
addresses the translation of out-of-vocabulary words by backing off to a
dictionary. In this paper, we introduce a simpler and more effective approach,
making the NMT model cap... | computer science |
15,540 | Analysis of Communication Pattern with Scammers in Enron Corpus | cs.CL | This paper is an exploratory analysis into fraud detection taking Enron email
corpus as the case study. The paper posits conclusions like strict servitude
and unquestionable faith among employees as breeding grounds for sham among
higher executives. We also try to infer on the nature of communication between
fraudulent... | computer science |
15,541 | On TimeML-Compliant Temporal Expression Extraction in Turkish | cs.CL | It is commonly acknowledged that temporal expression extractors are important
components of larger natural language processing systems like information
retrieval and question answering systems. Extraction and normalization of
temporal expressions in Turkish has not been given attention so far except the
extraction of s... | computer science |
15,542 | Encoding Prior Knowledge with Eigenword Embeddings | cs.CL | Canonical correlation analysis (CCA) is a method for reducing the dimension
of data represented using two views. It has been previously used to derive word
embeddings, where one view indicates a word, and the other view indicates its
context. We describe a way to incorporate prior knowledge into CCA, give a
theoretical... | computer science |
15,543 | The influence of Chunking on Dependency Crossing and Distance | cs.CL | This paper hypothesizes that chunking plays important role in reducing
dependency distance and dependency crossings. Computer simulations, when
compared with natural languages,show that chunking reduces mean dependency
distance (MDD) of a linear sequence of nodes (constrained by continuity or
projectivity) to that of n... | computer science |
15,544 | Take and Took, Gaggle and Goose, Book and Read: Evaluating the Utility
of Vector Differences for Lexical Relation Learning | cs.CL | Recent work on word embeddings has shown that simple vector subtraction over
pre-trained embeddings is surprisingly effective at capturing different lexical
relations, despite lacking explicit supervision. Prior work has evaluated this
intriguing result using a word analogy prediction formulation and hand-selected
rela... | computer science |
15,545 | A commentary on "The now-or-never bottleneck: a fundamental constraint
on language", by Christiansen and Chater (2016) | cs.CL | In a recent article, Christiansen and Chater (2016) present a fundamental
constraint on language, i.e. a now-or-never bottleneck that arises from our
fleeting memory, and explore its implications, e.g., chunk-and-pass processing,
outlining a framework that promises to unify different areas of research. Here
we explore ... | computer science |
15,546 | Integrate Document Ranking Information into Confidence Measure
Calculation for Spoken Term Detection | cs.CL | This paper proposes an algorithm to improve the calculation of confidence
measure for spoken term detection (STD). Given an input query term, the
algorithm first calculates a measurement named document ranking weight for each
document in the speech database to reflect its relevance with the query term by
summing all th... | computer science |
15,547 | Exploiting Out-of-Domain Data Sources for Dialectal Arabic Statistical
Machine Translation | cs.CL | Statistical machine translation for dialectal Arabic is characterized by a
lack of data since data acquisition involves the transcription and translation
of spoken language. In this study we develop techniques for extracting parallel
data for one particular dialect of Arabic (Iraqi Arabic) from out-of-domain
corpora in... | computer science |
15,548 | Unsupervised Discovery of Linguistic Structure Including Two-level
Acoustic Patterns Using Three Cascaded Stages of Iterative Optimization | cs.CL | Techniques for unsupervised discovery of acoustic patterns are getting
increasingly attractive, because huge quantities of speech data are becoming
available but manual annotations remain hard to acquire. In this paper, we
propose an approach for unsupervised discovery of linguistic structure for the
target spoken lang... | computer science |
15,549 | Unsupervised Spoken Term Detection with Spoken Queries by Multi-level
Acoustic Patterns with Varying Model Granularity | cs.CL | This paper presents a new approach for unsupervised Spoken Term Detection
with spoken queries using multiple sets of acoustic patterns automatically
discovered from the target corpus. The different pattern HMM
configurations(number of states per model, number of distinct models, number of
Gaussians per state)form a thr... | computer science |
15,550 | Enhancing Automatically Discovered Multi-level Acoustic Patterns
Considering Context Consistency With Applications in Spoken Term Detection | cs.CL | This paper presents a novel approach for enhancing the multiple sets of
acoustic patterns automatically discovered from a given corpus. In a previous
work it was proposed that different HMM configurations (number of states per
model, number of distinct models) for the acoustic patterns form a
two-dimensional space. Mul... | computer science |
15,551 | Probabilistic Bag-Of-Hyperlinks Model for Entity Linking | cs.CL | Many fundamental problems in natural language processing rely on determining
what entities appear in a given text. Commonly referenced as entity linking,
this step is a fundamental component of many NLP tasks such as text
understanding, automatic summarization, semantic search or machine translation.
Name ambiguity, wo... | computer science |
15,552 | Unsupervised Domain Discovery using Latent Dirichlet Allocation for
Acoustic Modelling in Speech Recognition | cs.CL | Speech recognition systems are often highly domain dependent, a fact widely
reported in the literature. However the concept of domain is complex and not
bound to clear criteria. Hence it is often not evident if data should be
considered to be out-of-domain. While both acoustic and language models can be
domain specific... | computer science |
15,553 | Towards Understanding Egyptian Arabic Dialogues | cs.CL | Labelling of user's utterances to understanding his attends which called
Dialogue Act (DA) classification, it is considered the key player for dialogue
language understanding layer in automatic dialogue systems. In this paper, we
proposed a novel approach to user's utterances labeling for Egyptian
spontaneous dialogues... | computer science |
15,554 | Verbs Taking Clausal and Non-Finite Arguments as Signals of Modality -
Revisiting the Issue of Meaning Grounded in Syntax | cs.CL | We revisit Levin's theory about the correspondence of verb meaning and syntax
and infer semantic classes from a large syntactic classification of more than
600 German verbs taking clausal and non-finite arguments. Grasping the meaning
components of Levin-classes is known to be hard. We address this challenge by
setting... | computer science |
15,555 | A Parallel Corpus of Translationese | cs.CL | We describe a set of bilingual English--French and English--German parallel
corpora in which the direction of translation is accurately and reliably
annotated. The corpora are diverse, consisting of parliamentary proceedings,
literary works, transcriptions of TED talks and political commentary. They will
be instrumenta... | computer science |
15,556 | Improving distant supervision using inference learning | cs.CL | Distant supervision is a widely applied approach to automatic training of
relation extraction systems and has the advantage that it can generate large
amounts of labelled data with minimal effort. However, this data may contain
errors and consequently systems trained using distant supervision tend not to
perform as wel... | computer science |
15,557 | The USFD Spoken Language Translation System for IWSLT 2014 | cs.CL | The University of Sheffield (USFD) participated in the International Workshop
for Spoken Language Translation (IWSLT) in 2014. In this paper, we will
introduce the USFD SLT system for IWSLT. Automatic speech recognition (ASR) is
achieved by two multi-pass deep neural network systems with adaptation and
rescoring techni... | computer science |
15,558 | Kannada named entity recognition and classification (nerc) based on
multinomial naïve bayes (mnb) classifier | cs.CL | Named Entity Recognition and Classification (NERC) is a process of
identification of proper nouns in the text and classification of those nouns
into certain predefined categories like person name, location, organization,
date, and time etc. NERC in Kannada is an essential and challenging task. The
aim of this work is t... | computer science |
15,559 | Dependency length minimization: Puzzles and Promises | cs.CL | In the recent issue of PNAS, Futrell et al. claims that their study of 37
languages gives the first large scale cross-language evidence for Dependency
Length Minimization, which is an overstatement that ignores similar previous
researches. In addition,this study seems to pay no attention to factors like
the uniformity ... | computer science |
15,560 | Splitting Compounds by Semantic Analogy | cs.CL | Compounding is a highly productive word-formation process in some languages
that is often problematic for natural language processing applications. In this
paper, we investigate whether distributional semantics in the form of word
embeddings can enable a deeper, i.e., more knowledge-rich, processing of
compounds than t... | computer science |
15,561 | TransG : A Generative Mixture Model for Knowledge Graph Embedding | cs.CL | Recently, knowledge graph embedding, which projects symbolic entities and
relations into continuous vector space, has become a new, hot topic in
artificial intelligence. This paper addresses a new issue of multiple relation
semantics that a relation may have multiple meanings revealed by the entity
pairs associated wit... | computer science |
15,562 | TransA: An Adaptive Approach for Knowledge Graph Embedding | cs.CL | Knowledge representation is a major topic in AI, and many studies attempt to
represent entities and relations of knowledge base in a continuous vector
space. Among these attempts, translation-based methods build entity and
relation vectors by minimizing the translation loss from a head entity to a
tail one. In spite of... | computer science |
15,563 | A Light Sliding-Window Part-of-Speech Tagger for the Apertium
Free/Open-Source Machine Translation Platform | cs.CL | This paper describes a free/open-source implementation of the light
sliding-window (LSW) part-of-speech tagger for the Apertium free/open-source
machine translation platform. Firstly, the mechanism and training process of
the tagger are reviewed, and a new method for incorporating linguistic rules is
proposed. Secondly... | computer science |
15,564 | Early text classification: a Naive solution | cs.CL | Text classification is a widely studied problem, and it can be considered
solved for some domains and under certain circumstances. There are scenarios,
however, that have received little or no attention at all, despite its
relevance and applicability. One of such scenarios is early text
classification, where one needs ... | computer science |
15,565 | Automatic Dialect Detection in Arabic Broadcast Speech | cs.CL | We investigate different approaches for dialect identification in Arabic
broadcast speech, using phonetic, lexical features obtained from a speech
recognition system, and acoustic features using the i-vector framework. We
studied both generative and discriminate classifiers, and we combined these
features using a multi... | computer science |
15,566 | Fully automatic multi-language translation with a catalogue of phrases -
successful employment for the Swiss avalanche bulletin | cs.CL | The Swiss avalanche bulletin is produced twice a day in four languages. Due
to the lack of time available for manual translation, a fully automated
translation system is employed, based on a catalogue of predefined phrases and
predetermined rules of how these phrases can be combined to produce sentences.
Because this c... | computer science |
15,567 | Bilingual Distributed Word Representations from Document-Aligned
Comparable Data | cs.CL | We propose a new model for learning bilingual word representations from
non-parallel document-aligned data. Following the recent advances in word
representation learning, our model learns dense real-valued word vectors, that
is, bilingual word embeddings (BWEs). Unlike prior work on inducing BWEs which
heavily relied o... | computer science |
15,568 | Description of the Odin Event Extraction Framework and Rule Language | cs.CL | This document describes the Odin framework, which is a domain-independent
platform for developing rule-based event extraction models. Odin aims to be
powerful (the rule language allows the modeling of complex syntactic
structures) and robust (to recover from syntactic parsing errors, syntactic
patterns can be freely mi... | computer science |
15,569 | Sentiment Uncertainty and Spam in Twitter Streams and Its Implications
for General Purpose Realtime Sentiment Analysis | cs.CL | State of the art benchmarks for Twitter Sentiment Analysis do not consider
the fact that for more than half of the tweets from the public stream a
distinct sentiment cannot be chosen. This paper provides a new perspective on
Twitter Sentiment Analysis by highlighting the necessity of explicitly
incorporating uncertaint... | computer science |
15,570 | Sentiment of Emojis | cs.CL | There is a new generation of emoticons, called emojis, that is increasingly
being used in mobile communications and social media. In the past two years,
over ten billion emojis were used on Twitter. Emojis are Unicode graphic
symbols, used as a shorthand to express concepts and ideas. In contrast to the
small number of... | computer science |
15,571 | Automatically Segmenting Oral History Transcripts | cs.CL | Dividing oral histories into topically coherent segments can make them more
accessible online. People regularly make judgments about where coherent
segments can be extracted from oral histories. But making these judgments can
be taxing, so automated assistance is potentially attractive to speed the task
of extracting s... | computer science |
15,572 | Polish - English Speech Statistical Machine Translation Systems for the
IWSLT 2014 | cs.CL | This research explores effects of various training settings between Polish
and English Statistical Machine Translation systems for spoken language.
Various elements of the TED parallel text corpora for the IWSLT 2014 evaluation
campaign were used as the basis for training of language models, and for
development, tuning... | computer science |
15,573 | The "handedness" of language: Directional symmetry breaking of sign
usage in words | cs.CL | Language, which allows complex ideas to be communicated through symbolic
sequences, is a characteristic feature of our species and manifested in a
multitude of forms. Using large written corpora for many different languages
and scripts, we show that the occurrence probability distributions of signs at
the left and righ... | computer science |
15,574 | Determination of the Internet Anonymity Influence on the Level of
Aggression and Usage of Obscene Lexis | cs.CL | This article deals with the analysis of the semantic content of the anonymous
Russian-speaking forum 2ch.hk, different verbal means of expressing of the
emotional state of aggression are revealed for this site, and aggression is
classified by its directions. The lexis of different Russian-and English-
speaking anonymou... | computer science |
15,575 | Response to Liu, Xu, and Liang (2015) and Ferrer-i-Cancho and
Gómez-Rodríguez (2015) on Dependency Length Minimization | cs.CL | We address recent criticisms (Liu et al., 2015; Ferrer-i-Cancho and
G\'omez-Rodr\'iguez, 2015) of our work on empirical evidence of dependency
length minimization across languages (Futrell et al., 2015). First, we
acknowledge error in failing to acknowledge Liu (2008)'s previous work on
corpora of 20 languages with sim... | computer science |
15,576 | Automatic Taxonomy Extraction from Query Logs with no Additional Sources
of Information | cs.CL | Search engine logs store detailed information on Web users interactions.
Thus, as more and more people use search engines on a daily basis, important
trails of users common knowledge are being recorded in those files. Previous
research has shown that it is possible to extract concept taxonomies from full
text documents... | computer science |
15,577 | A Primer on Neural Network Models for Natural Language Processing | cs.CL | Over the past few years, neural networks have re-emerged as powerful
machine-learning models, yielding state-of-the-art results in fields such as
image recognition and speech processing. More recently, neural network models
started to be applied also to textual natural language signals, again with very
promising result... | computer science |
15,578 | It is not all downhill from here: Syllable Contact Law in Persian | cs.CL | Syllable contact pairs crosslinguistically tend to have a falling sonority
slope a constraint which is called the Syllable Contact Law SCL In this study
the phonotactics of syllable contacts in 4202 CVCCVC words of Persian lexicon
is investigated The consonants of Persian were divided into five sonority
categories and ... | computer science |
15,579 | P-trac Procedure: The Dispersion and Neutralization of Contrasts in
Lexicon | cs.CL | Cognitive acoustic cues have an important role in shaping the phonological
structure of language as a means to optimal communication. In this paper we
introduced P-trac procedure in order to track dispersion of contrasts in
different contexts in lexicon. The results of applying P-trac procedure to the
case of dispersio... | computer science |
15,580 | Deep convolutional acoustic word embeddings using word-pair side
information | cs.CL | Recent studies have been revisiting whole words as the basic modelling unit
in speech recognition and query applications, instead of phonetic units. Such
whole-word segmental systems rely on a function that maps a variable-length
speech segment to a vector in a fixed-dimensional space; the resulting acoustic
word embed... | computer science |
15,581 | Analyzer and generator for Pali | cs.CL | This work describes a system that performs morphological analysis and
generation of Pali words. The system works with regular inflectional paradigms
and a lexical database. The generator is used to build a collection of
inflected and derived words, which in turn is used by the analyzer. Generating
and storing morpholog... | computer science |
15,582 | Language Segmentation | cs.CL | Language segmentation consists in finding the boundaries where one language
ends and another language begins in a text written in more than one language.
This is important for all natural language processing tasks. The problem can be
solved by training language models on language data. However, in the case of
low- or n... | computer science |
15,583 | Using Ontology-Based Context in the Portuguese-English Translation of
Homographs in Textual Dialogues | cs.CL | This paper introduces a novel approach to tackle the existing gap on message
translations in dialogue systems. Currently, submitted messages to the dialogue
systems are considered as isolated sentences. Thus, missing context information
impede the disambiguation of homographs words in ambiguous sentences. Our
approach ... | computer science |
15,584 | Assisting Composition of Email Responses: a Topic Prediction Approach | cs.CL | We propose an approach for helping agents compose email replies to customer
requests. To enable that, we use LDA to extract latent topics from a collection
of email exchanges. We then use these latent topics to label our data,
obtaining a so-called "silver standard" topic labelling. We exploit this
labelled set to trai... | computer science |
15,585 | Resolving References to Objects in Photographs using the
Words-As-Classifiers Model | cs.CL | A common use of language is to refer to visually present objects. Modelling
it in computers requires modelling the link between language and perception.
The "words as classifiers" model of grounded semantics views words as
classifiers of perceptual contexts, and composes the meaning of a phrase
through composition of t... | computer science |
15,586 | Automata networks for multi-party communication in the Naming Game | cs.CL | The Naming Game has been studied to explore the role of self-organization in
the development and negotiation of linguistic conventions. In this paper, we
define an automata networks approach to the Naming Game. Two problems are
faced: (1) the definition of an automata networks for multi-party communicative
interactions... | computer science |
15,587 | Controlled Experiments for Word Embeddings | cs.CL | An experimental approach to studying the properties of word embeddings is
proposed. Controlled experiments, achieved through modifications of the
training corpus, permit the demonstration of direct relations between word
properties and word vector direction and length. The approach is demonstrated
using the word2vec CB... | computer science |
15,588 | Human languages order information efficiently | cs.CL | Most languages use the relative order between words to encode meaning
relations. Languages differ, however, in what orders they use and how these
orders are mapped onto different meanings. We test the hypothesis that, despite
these differences, human languages might constitute different `solutions' to
common pressures ... | computer science |
15,589 | A Diversity-Promoting Objective Function for Neural Conversation Models | cs.CL | Sequence-to-sequence neural network models for generation of conversational
responses tend to generate safe, commonplace responses (e.g., "I don't know")
regardless of the input. We suggest that the traditional objective function,
i.e., the likelihood of output (response) given input (message) is unsuited to
response g... | computer science |
15,590 | Towards Meaningful Maps of Polish Case Law | cs.CL | In this work, we analyze the utility of two dimensional document maps for
exploratory analysis of Polish case law. We start by comparing two methods of
generating such visualizations. First is based on linear principal component
analysis (PCA). Second makes use of the modern nonlinear t-Distributed
Stochastic Neighbor ... | computer science |
15,591 | Bridge Correlational Neural Networks for Multilingual Multimodal
Representation Learning | cs.CL | Recently there has been a lot of interest in learning common representations
for multiple views of data. Typically, such common representations are learned
using a parallel corpus between the two views (say, 1M images and their English
captions). In this work, we address a real-world scenario where no direct
parallel d... | computer science |
15,592 | Hybrid Dialog State Tracker | cs.CL | This paper presents a hybrid dialog state tracker that combines a rule based
and a machine learning based approach to belief state tracking. Therefore, we
call it a hybrid tracker. The machine learning in our tracker is realized by a
Long Short Term Memory (LSTM) network. To our knowledge, our hybrid tracker
sets a new... | computer science |
15,593 | Improved Deep Learning Baselines for Ubuntu Corpus Dialogs | cs.CL | This paper presents results of our experiments for the next utterance ranking
on the Ubuntu Dialog Corpus -- the largest publicly available multi-turn dialog
corpus. First, we use an in-house implementation of previously reported models
to do an independent evaluation using the same data. Second, we evaluate the
perfor... | computer science |
15,594 | Noisy-parallel and comparable corpora filtering methodology for the
extraction of bi-lingual equivalent data at sentence level | cs.CL | Text alignment and text quality are critical to the accuracy of Machine
Translation (MT) systems, some NLP tools, and any other text processing tasks
requiring bilingual data. This research proposes a language independent
bi-sentence filtering approach based on Polish (not a position-sensitive
language) to English expe... | computer science |
15,595 | Telemedicine as a special case of Machine Translation | cs.CL | Machine translation is evolving quite rapidly in terms of quality. Nowadays,
we have several machine translation systems available in the web, which provide
reasonable translations. However, these systems are not perfect, and their
quality may decrease in some specific domains. This paper examines the effects
of differ... | computer science |
15,596 | A Method for Modeling Co-Occurrence Propensity of Clinical Codes with
Application to ICD-10-PCS Auto-Coding | cs.CL | Objective. Natural language processing methods for medical auto-coding, or
automatic generation of medical billing codes from electronic health records,
generally assign each code independently of the others. They may thus assign
codes for closely related procedures or diagnoses to the same document, even
when they do ... | computer science |
15,597 | Neural Reranking Improves Subjective Quality of Machine Translation:
NAIST at WAT2015 | cs.CL | This year, the Nara Institute of Science and Technology (NAIST)'s submission
to the 2015 Workshop on Asian Translation was based on syntax-based statistical
machine translation, with the addition of a reranking component using neural
attentional machine translation models. Experiments re-confirmed results from
previous... | computer science |
15,598 | Part-of-Speech Tagging with Bidirectional Long Short-Term Memory
Recurrent Neural Network | cs.CL | Bidirectional Long Short-Term Memory Recurrent Neural Network (BLSTM-RNN) has
been shown to be very effective for tagging sequential data, e.g. speech
utterances or handwritten documents. While word embedding has been demoed as a
powerful representation for characterizing the statistical properties of
natural language.... | computer science |
15,599 | Learning in the Rational Speech Acts Model | cs.CL | The Rational Speech Acts (RSA) model treats language use as a recursive
process in which probabilistic speaker and listener agents reason about each
other's intentions to enrich the literal semantics of their language along
broadly Gricean lines. RSA has been shown to capture many kinds of
conversational implicature, b... | computer science |
15,600 | Combine CRF and MMSEG to Boost Chinese Word Segmentation in Social Media | cs.CL | In this paper, we propose a joint algorithm for the word segmentation on
Chinese social media. Previous work mainly focus on word segmentation for plain
Chinese text, in order to develop a Chinese social media processing tool, we
need to take the main features of social media into account, whose grammatical
structure i... | computer science |
15,601 | Statistical Parsing by Machine Learning from a Classical Arabic Treebank | cs.CL | Research into statistical parsing for English has enjoyed over a decade of
successful results. However, adapting these models to other languages has met
with difficulties. Previous comparative work has shown that Modern Arabic is
one of the most difficult languages to parse due to rich morphology and free
word order. C... | computer science |
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