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34,404 | Introducing a Calculus of Effects and Handlers for Natural Language
Semantics | cs.CL | In compositional model-theoretic semantics, researchers assemble
truth-conditions or other kinds of denotations using the lambda calculus. It
was previously observed that the lambda terms and/or the denotations studied
tend to follow the same pattern: they are instances of a monad. In this paper,
we present an extensio... | computer science |
34,405 | MOSI: Multimodal Corpus of Sentiment Intensity and Subjectivity Analysis
in Online Opinion Videos | cs.CL | People are sharing their opinions, stories and reviews through online video
sharing websites every day. Studying sentiment and subjectivity in these
opinion videos is experiencing a growing attention from academia and industry.
While sentiment analysis has been successful for text, it is an understudied
research questi... | computer science |
34,406 | An empirical study on large scale text classification with skip-gram
embeddings | cs.CL | We investigate the integration of word embeddings as classification features
in the setting of large scale text classification. Such representations have
been used in a plethora of tasks, however their application in classification
scenarios with thousands of classes has not been extensively researched,
partially due t... | computer science |
34,407 | Criticality in Formal Languages and Statistical Physics | cs.CL | We show that the mutual information between two symbols, as a function of the
number of symbols between the two, decays exponentially in any probabilistic
regular grammar, but can decay like a power law for a context-free grammar.
This result about formal languages is closely related to a well-known result in
classical... | computer science |
34,408 | Learning text representation using recurrent convolutional neural
network with highway layers | cs.CL | Recently, the rapid development of word embedding and neural networks has
brought new inspiration to various NLP and IR tasks. In this paper, we describe
a staged hybrid model combining Recurrent Convolutional Neural Networks (RCNN)
with highway layers. The highway network module is incorporated in the middle
takes the... | computer science |
34,409 | Toward Word Embedding for Personalized Information Retrieval | cs.IR | This paper presents preliminary works on using Word Embedding (word2vec) for
query expansion in the context of Personalized Information Retrieval.
Traditionally, word embeddings are learned on a general corpus, like Wikipedia.
In this work we try to personalize the word embeddings learning, by achieving
the learning on... | computer science |
34,410 | Using Word Embeddings in Twitter Election Classification | cs.IR | Word embeddings and convolutional neural networks (CNN) have attracted
extensive attention in various classification tasks for Twitter, e.g. sentiment
classification. However, the effect of the configuration used to train and
generate the word embeddings on the classification performance has not been
studied in the exi... | computer science |
34,411 | Deep Feature Fusion Network for Answer Quality Prediction in Community
Question Answering | cs.IR | Community Question Answering (cQA) forums have become a popular medium for
soliciting direct answers to specific questions of users from experts or other
experienced users on a given topic. However, for a given question, users
sometimes have to sift through a large number of low-quality or irrelevant
answers to find ou... | computer science |
34,412 | Toward a Deep Neural Approach for Knowledge-Based IR | cs.IR | This paper tackles the problem of the semantic gap between a document and a
query within an ad-hoc information retrieval task. In this context, knowledge
bases (KBs) have already been acknowledged as valuable means since they allow
the representation of explicit relations between entities. However, they do not
necessar... | computer science |
34,413 | Adaptability of Neural Networks on Varying Granularity IR Tasks | cs.IR | Recent work in Information Retrieval (IR) using Deep Learning models has
yielded state of the art results on a variety of IR tasks. Deep neural networks
(DNN) are capable of learning ideal representations of data during the training
process, removing the need for independently extracting features. However, the
structur... | computer science |
34,414 | Efficient Parallel Learning of Word2Vec | cs.CL | Since its introduction, Word2Vec and its variants are widely used to learn
semantics-preserving representations of words or entities in an embedding
space, which can be used to produce state-of-art results for various Natural
Language Processing tasks. Existing implementations aim to learn efficiently by
running multip... | computer science |
34,415 | Hierarchical Neural Language Models for Joint Representation of
Streaming Documents and their Content | cs.CL | We consider the problem of learning distributed representations for documents
in data streams. The documents are represented as low-dimensional vectors and
are jointly learned with distributed vector representations of word tokens
using a hierarchical framework with two embedded neural language models. In
particular, w... | computer science |
34,416 | Representation learning for very short texts using weighted word
embedding aggregation | cs.IR | Short text messages such as tweets are very noisy and sparse in their use of
vocabulary. Traditional textual representations, such as tf-idf, have
difficulty grasping the semantic meaning of such texts, which is important in
applications such as event detection, opinion mining, news recommendation, etc.
We constructed ... | computer science |
34,417 | A Maturity Model for Public Administration as Open Translation Data
Providers | cs.CY | Any public administration that produces translation data can be a provider of
useful reusable data to meet its own translation needs and the ones of other
public organizations and private companies that work with texts of the same
domain. These data can also be crucial to produce domain-tuned Machine
Translation system... | computer science |
34,418 | Lexical Based Semantic Orientation of Online Customer Reviews and Blogs | cs.CL | Rapid increase in internet users along with growing power of online review
sites and social media has given birth to sentiment analysis or opinion mining,
which aims at determining what other people think and comment. Sentiments or
Opinions contain public generated content about products, services, policies
and politic... | computer science |
34,419 | Actionable and Political Text Classification using Word Embeddings and
LSTM | cs.CL | In this work, we apply word embeddings and neural networks with Long
Short-Term Memory (LSTM) to text classification problems, where the
classification criteria are decided by the context of the application. We
examine two applications in particular. The first is that of Actionability,
where we build models to classify... | computer science |
34,420 | Exploring the Political Agenda of the European Parliament Using a
Dynamic Topic Modeling Approach | cs.CL | This study analyzes the political agenda of the European Parliament (EP)
plenary, how it has evolved over time, and the manner in which Members of the
European Parliament (MEPs) have reacted to external and internal stimuli when
making plenary speeches. To unveil the plenary agenda and detect latent themes
in legislati... | computer science |
34,421 | AudioPairBank: Towards A Large-Scale Tag-Pair-Based Audio Content
Analysis | cs.SD | Recently, sound recognition has been used to identify sounds, such as car and
river. However, sounds have nuances that may be better described by
adjective-noun pairs such as slow car, and verb-noun pairs such as flying
insects, which are under explored. Therefore, in this work we investigate the
relation between audio... | computer science |
34,422 | Tie-breaker: Using language models to quantify gender bias in sports
journalism | cs.CL | Gender bias is an increasingly important issue in sports journalism. In this
work, we propose a language-model-based approach to quantify differences in
questions posed to female vs. male athletes, and apply it to tennis post-match
interviews. We find that journalists ask male players questions that are
generally more ... | computer science |
34,423 | Identification of promising research directions using machine learning
aided medical literature analysis | cs.CL | The rapidly expanding corpus of medical research literature presents major
challenges in the understanding of previous work, the extraction of maximum
information from collected data, and the identification of promising research
directions. We present a case for the use of advanced machine learning
techniques as an aid... | computer science |
34,424 | A Novel Information Theoretic Framework for Finding Semantic Similarity
in WordNet | cs.IR | Information content (IC) based measures for finding semantic similarity is
gaining preferences day by day. Semantics of concepts can be highly
characterized by information theory. The conventional way for calculating IC is
based on the probability of appearance of concepts in corpora. Due to data
sparseness and corpora... | computer science |
34,425 | A Supervised Authorship Attribution Framework for Bengali Language | cs.CL | Authorship Attribution is a long-standing problem in Natural Language
Processing. Several statistical and computational methods have been used to
find a solution to this problem. In this paper, we have proposed methods to
deal with the authorship attribution problem in Bengali. | computer science |
34,426 | How scientific literature has been evolving over the time? A novel
statistical approach using tracking verbal-based methods | cs.CL | This paper provides a global vision of the scientific publications related
with the Systemic Lupus Erythematosus (SLE), taking as starting point abstracts
of articles. Through the time, abstracts have been evolving towards higher
complexity on used terminology, which makes necessary the use of sophisticated
statistical... | computer science |
34,427 | Labeling of Query Words using Conditional Random Field | cs.IR | This paper describes our approach on Query Word Labeling as an attempt in the
shared task on Mixed Script Information Retrieval at Forum for Information
Retrieval Evaluation (FIRE) 2015. The query is written in Roman script and the
words were in English or transliterated from Indian regional languages. A total
of eight... | computer science |
34,428 | Evolutionary forces in language change | cs.CL | Languages and genes are both transmitted from generation to generation, with
opportunity for differential reproduction and survivorship of forms. Here we
apply a rigorous inference framework, drawn from population genetics, to
distinguish between two broad mechanisms of language change: drift and
selection. Drift is ch... | computer science |
34,429 | Query Clustering using Segment Specific Context Embeddings | cs.IR | This paper presents a novel query clustering approach to capture the broad
interest areas of users querying search engines. We make use of recent advances
in NLP - word2vec and extend it to get query2vec, vector representations of
queries, based on query contexts, obtained from the top search results for the
query and ... | computer science |
34,430 | Quantum Algorithms for Compositional Natural Language Processing | cs.CL | We propose a new application of quantum computing to the field of natural
language processing. Ongoing work in this field attempts to incorporate
grammatical structure into algorithms that compute meaning. In (Coecke,
Sadrzadeh and Clark, 2010), the authors introduce such a model (the CSC model)
based on tensor product... | computer science |
34,431 | Bridging the Gap: Incorporating a Semantic Similarity Measure for
Effectively Mapping PubMed Queries to Documents | cs.CL | The main approach of traditional information retrieval (IR) is to examine how
many words from a query appear in a document. A drawback of this approach,
however, is that it may fail to detect relevant documents where no or only few
words from a query are found. The semantic analysis methods such as LSA (latent
semantic... | computer science |
34,432 | OCR of historical printings with an application to building diachronic
corpora: A case study using the RIDGES herbal corpus | cs.CL | This article describes the results of a case study that applies Neural
Network-based Optical Character Recognition (OCR) to scanned images of books
printed between 1487 and 1870 by training the OCR engine OCRopus
[@breuel2013high] on the RIDGES herbal text corpus [@OdebrechtEtAlSubmitted].
Training specific OCR models ... | computer science |
34,433 | Automating Political Bias Prediction | cs.SI | Every day media generate large amounts of text. An unbiased view on media
reports requires an understanding of the political bias of media content.
Assistive technology for estimating the political bias of texts can be helpful
in this context. This study proposes a simple statistical learning approach to
predict politi... | computer science |
34,434 | Reconciling Lambek's restriction, cut-elimination, and substitution in
the presence of exponential modalities | math.LO | The Lambek calculus can be considered as a version of non-commutative
intuitionistic linear logic. One of the interesting features of the Lambek
calculus is the so-called "Lambek's restriction," that is, the antecedent of
any provable sequent should be non-empty. In this paper we discuss ways of
extending the Lambek ca... | computer science |
34,435 | Incorporation of Speech Duration Information in Score Fusion of Speaker
Recognition Systems | cs.SD | In recent years identity-vector (i-vector) based speaker verification (SV)
systems have become very successful. Nevertheless, environmental noise and
speech duration variability still have a significant effect on degrading the
performance of these systems. In many real-life applications, duration of
recordings are very... | computer science |
34,436 | Topic Modelling and Event Identification from Twitter Textual Data | cs.SI | The tremendous growth of social media content on the Internet has inspired
the development of the text analytics to understand and solve real-life
problems. Leveraging statistical topic modelling helps researchers and
practitioners in better comprehension of textual content as well as provides
useful information for fu... | computer science |
34,437 | TweeTime: A Minimally Supervised Method for Recognizing and Normalizing
Time Expressions in Twitter | cs.IR | We describe TweeTIME, a temporal tagger for recognizing and normalizing time
expressions in Twitter. Most previous work in social media analysis has to rely
on temporal resolvers that are designed for well-edited text, and therefore
suffer from the reduced performance due to domain mismatch. We present a
minimally supe... | computer science |
34,438 | Growing Graphs with Hyperedge Replacement Graph Grammars | cs.SI | Discovering the underlying structures present in large real world graphs is a
fundamental scientific problem. In this paper we show that a graph's clique
tree can be used to extract a hyperedge replacement grammar. If we store an
ordering from the extraction process, the extracted graph grammar is guaranteed
to generat... | computer science |
34,439 | Extracting Biological Pathway Models From NLP Event Representations | cs.CL | This paper describes an an open-source software system for the automatic
conversion of NLP event representations to system biology structured data
interchange formats such as SBML and BioPAX. It is part of a larger effort to
make results of the NLP community available for system biology pathway
modelers. | computer science |
34,440 | Measuring the State of the Art of Automated Pathway Curation Using Graph
Algorithms - A Case Study of the mTOR Pathway | cs.CL | This paper evaluates the difference between human pathway curation and
current NLP systems. We propose graph analysis methods for quantifying the gap
between human curated pathway maps and the output of state-of-the-art automatic
NLP systems. Evaluation is performed on the popular mTOR pathway. Based on
analyzing where... | computer science |
34,441 | Undecidability of the Lambek calculus with subexponential and bracket
modalities | math.LO | The Lambek calculus is a well-known logical formalism for modelling natural
language syntax. The original calculus covered a substantial number of
intricate natural language phenomena, but only those restricted to the
context-free setting. In order to address more subtle linguistic issues, the
Lambek calculus has been ... | computer science |
34,442 | Attribute Extraction from Product Titles in eCommerce | cs.CL | This paper presents a named entity extraction system for detecting attributes
in product titles of eCommerce retailers like Walmart. The absence of syntactic
structure in such short pieces of text makes extracting attribute values a
challenging problem. We find that combining sequence labeling algorithms such
as Condit... | computer science |
34,443 | Learning Latent Local Conversation Modes for Predicting Community
Endorsement in Online Discussions | cs.SI | Many social media platforms offer a mechanism for readers to react to
comments, both positively and negatively, which in aggregate can be thought of
as community endorsement. This paper addresses the problem of predicting
community endorsement in online discussions, leveraging both the participant
response structure an... | computer science |
34,444 | Tracking Amendments to Legislation and Other Political Texts with a
Novel Minimum-Edit-Distance Algorithm: DocuToads | cs.CL | Political scientists often find themselves tracking amendments to political
texts. As different actors weigh in, texts change as they are drafted and
redrafted, reflecting political preferences and power. This study provides a
novel solution to the prob- lem of detecting amendments to political text based
upon minimum ... | computer science |
34,445 | Using Semantic Similarity for Input Topic Identification in
Crawling-based Web Application Testing | cs.SE | To automatically test web applications, crawling-based techniques are usually
adopted to mine the behavior models, explore the state spaces or detect the
violated invariants of the applications. However, in existing crawlers, rules
for identifying the topics of input text fields, such as login ids, passwords,
emails, d... | computer science |
34,446 | Lexical Query Modeling in Session Search | cs.IR | Lexical query modeling has been the leading paradigm for session search. In
this paper, we analyze TREC session query logs and compare the performance of
different lexical matching approaches for session search. Naive methods based
on term frequency weighing perform on par with specialized session models. In
addition, ... | computer science |
34,447 | A Novel Term_Class Relevance Measure for Text Categorization | cs.IR | In this paper, we introduce a new measure called Term_Class relevance to
compute the relevancy of a term in classifying a document into a particular
class. The proposed measure estimates the degree of relevance of a given term,
in placing an unlabeled document to be a member of a known class, as a product
of Class_Term... | computer science |
34,448 | All Fingers are not Equal: Intensity of References in Scientific
Articles | cs.CL | Research accomplishment is usually measured by considering all citations with
equal importance, thus ignoring the wide variety of purposes an article is
being cited for. Here, we posit that measuring the intensity of a reference is
crucial not only to perceive better understanding of research endeavor, but
also to impr... | computer science |
34,449 | Identifying Dogmatism in Social Media: Signals and Models | cs.CL | We explore linguistic and behavioral features of dogmatism in social media
and construct statistical models that can identify dogmatic comments. Our model
is based on a corpus of Reddit posts, collected across a diverse set of
conversational topics and annotated via paid crowdsourcing. We operationalize
key aspects of ... | computer science |
34,450 | Citation Classification for Behavioral Analysis of a Scientific Field | cs.CL | Citations are an important indicator of the state of a scientific field,
reflecting how authors frame their work, and influencing uptake by future
scholars. However, our understanding of citation behavior has been limited to
small-scale manual citation analysis. We perform the largest behavioral study
of citations to d... | computer science |
34,451 | SynsetRank: Degree-adjusted Random Walk for Relation Identification | cs.CL | In relation extraction, a key process is to obtain good detectors that find
relevant sentences describing the target relation. To minimize the necessity of
labeled data for refining detectors, previous work successfully made use of
BabelNet, a semantic graph structure expressing relationships between synsets,
as side i... | computer science |
34,452 | Lexical-Morphological Modeling for Legal Text Analysis | cs.IR | In the context of the Competition on Legal Information Extraction/Entailment
(COLIEE), we propose a method comprising the necessary steps for finding
relevant documents to a legal question and deciding on textual entailment
evidence to provide a correct answer. The proposed method is based on the
combination of several... | computer science |
34,453 | Automatically extracting, ranking and visually summarizing the
treatments for a disease | cs.CL | Clinicians are expected to have up-to-date and broad knowledge of disease
treatment options for a patient. Online health knowledge resources contain a
wealth of information. However, because of the time investment needed to
disseminate and rank pertinent information, there is a need to summarize the
information in a mo... | computer science |
34,454 | Using Natural Language Processing to Screen Patients with Active Heart
Failure: An Exploration for Hospital-wide Surveillance | cs.CL | In this paper, we proposed two different approaches, a rule-based approach
and a machine-learning based approach, to identify active heart failure cases
automatically by analyzing electronic health records (EHR). For the rule-based
approach, we extracted cardiovascular data elements from clinical notes and
matched pati... | computer science |
34,455 | CRTS: A type system for representing clinical recommendations | cs.CL | Background: Clinical guidelines and recommendations are the driving wheels of
the evidence-based medicine (EBM) paradigm, but these are available primarily
as unstructured text and are generally highly heterogeneous in nature. This
significantly reduces the dissemination and automatic application of these
recommendatio... | computer science |
34,456 | An Information Extraction Approach to Prescreen Heart Failure Patients
for Clinical Trials | cs.CL | To reduce the large amount of time spent screening, identifying, and
recruiting patients into clinical trials, we need prescreening systems that are
able to automate the data extraction and decision-making tasks that are
typically relegated to clinical research study coordinators. However, a major
obstacle is the vast ... | computer science |
34,457 | A Hybrid Citation Retrieval Algorithm for Evidence-based Clinical
Knowledge Summarization: Combining Concept Extraction, Vector Similarity and
Query Expansion for High Precision | cs.CL | Novel information retrieval methods to identify citations relevant to a
clinical topic can overcome the knowledge gap existing between the primary
literature (MEDLINE) and online clinical knowledge resources such as UpToDate.
Searching the MEDLINE database directly or with query expansion methods returns
a large number... | computer science |
34,458 | Divide and...conquer? On the limits of algorithmic approaches to
syntactic semantic structure | cs.CL | In computer science, divide and conquer (D&C) is an algorithm design paradigm
based on multi-branched recursion. A D&C algorithm works by recursively and
monotonically breaking down a problem into sub problems of the same (or a
related) type, until these become simple enough to be solved directly. The
solutions to the ... | computer science |
34,459 | An Adaptive Psychoacoustic Model for Automatic Speech Recognition | cs.CL | Compared with automatic speech recognition (ASR), the human auditory system
is more adept at handling noise-adverse situations, including environmental
noise and channel distortion. To mimic this adeptness, auditory models have
been widely incorporated in ASR systems to improve their robustness. This paper
proposes a n... | computer science |
34,460 | Intrinsic normalization and extrinsic denormalization of formant data of
vowels | cs.SD | Using a known speaker-intrinsic normalization procedure, formant data are
scaled by the reciprocal of the geometric mean of the first three formant
frequencies. This reduces the influence of the talker but results in a
distorted vowel space. The proposed speaker-extrinsic procedure re-scales the
normalized values by th... | computer science |
34,461 | Interactive Spoken Content Retrieval by Deep Reinforcement Learning | cs.CL | User-machine interaction is important for spoken content retrieval. For text
content retrieval, the user can easily scan through and select on a list of
retrieved item. This is impossible for spoken content retrieval, because the
retrieved items are difficult to show on screen. Besides, due to the high
degree of uncert... | computer science |
34,462 | Select-Additive Learning: Improving Generalization in Multimodal
Sentiment Analysis | cs.CL | Multimodal sentiment analysis is drawing an increasing amount of attention
these days. It enables mining of opinions in video reviews which are now
available aplenty on online platforms. However, multimodal sentiment analysis
has only a few high-quality data sets annotated for training machine learning
algorithms. Thes... | computer science |
34,463 | KU-ISPL Language Recognition System for NIST 2015 i-Vector Machine
Learning Challenge | cs.SD | In language recognition, the task of rejecting/differentiating closely spaced
versus acoustically far spaced languages remains a major challenge. For
confusable closely spaced languages, the system needs longer input test
duration material to obtain sufficient information to distinguish between
languages. Alternatively... | computer science |
34,464 | A New Statistic Feature of the Short-Time Amplitude Spectrum Values for
Human's Unvoiced Pronunciation | cs.SD | In this paper, a new statistic feature of the discrete short-time amplitude
spectrum is discovered by experiments for the signals of unvoiced
pronunciation. For the random-varying short-time spectrum, this feature reveals
the relationship between the amplitude's average and its standard for every
frequency component. O... | computer science |
34,465 | Speaker Recognition for Children's Speech | cs.SD | This paper presents results on Speaker Recognition (SR) for children's
speech, using the OGI Kids corpus and GMM-UBM and GMM-SVM SR systems. Regions
of the spectrum containing important speaker information for children are
identified by conducting SR experiments over 21 frequency bands. As for adults,
the spectrum can ... | computer science |
34,466 | Existence of Hierarchies and Human's Pursuit of Top Hierarchy Lead to
Power Law | cs.CL | The power law is ubiquitous in natural and social phenomena, and is
considered as a universal relationship between the frequency and its rank for
diverse social systems. However, a general model is still lacking to interpret
why these seemingly unrelated systems share great similarity. Through a
detailed analysis of na... | computer science |
34,467 | A Hackathon for Classical Tibetan | cs.CL | We describe the course of a hackathon dedicated to the development of
linguistic tools for Tibetan Buddhist studies. Over a period of five days, a
group of seventeen scholars, scientists, and students developed and compared
algorithms for intertextual alignment and text classification, along with some
basic language to... | computer science |
34,468 | Local Training for PLDA in Speaker Verification | cs.SD | PLDA is a popular normalization approach for the i-vector model, and it has
delivered state-of-the-art performance in speaker verification. However, PLDA
training requires a large amount of labeled development data, which is highly
expensive in most cases. A possible approach to mitigate the problem is various
unsuperv... | computer science |
34,469 | Collaborative Learning for Language and Speaker Recognition | cs.SD | This paper presents a unified model to perform language and speaker
recognition simultaneously and altogether. The model is based on a multi-task
recurrent neural network where the output of one task is fed as the input of
the other, leading to a collaborative learning framework that can improve both
language and speak... | computer science |
34,470 | WS4A: a Biomedical Question and Answering System based on public Web
Services and Ontologies | cs.CL | This paper describes our system, dubbed WS4A (Web Services for All), that
participated in the fourth edition of the BioASQ challenge (2016). We used WS4A
to perform the Question and Answering (QA) task 4b, which consisted on the
retrieval of relevant concepts, documents, snippets, RDF triples, exact answers
and ideal a... | computer science |
34,471 | Using Natural Language Processing and Qualitative Analysis to Intervene
in Gang Violence: A Collaboration Between Social Work Researchers and Data
Scientists | cs.CY | The U.S. has the highest rate of firearm-related deaths when compared to
other industrialized countries. Violence particularly affects low-income, urban
neighborhoods in cities like Chicago, which saw a 40% increase in firearm
violence from 2014 to 2015 to more than 3,000 shooting victims. While recent
studies have fou... | computer science |
34,472 | Stance Classification in Rumours as a Sequential Task Exploiting the
Tree Structure of Social Media Conversations | cs.CL | Rumour stance classification, the task that determines if each tweet in a
collection discussing a rumour is supporting, denying, questioning or simply
commenting on the rumour, has been attracting substantial interest. Here we
introduce a novel approach that makes use of the sequence of transitions
observed in tree-str... | computer science |
34,473 | An Arabic-Hebrew parallel corpus of TED talks | cs.CL | We describe an Arabic-Hebrew parallel corpus of TED talks built upon WIT3,
the Web inventory that repurposes the original content of the TED website in a
way which is more convenient for MT researchers. The benchmark consists of
about 2,000 talks, whose subtitles in Arabic and Hebrew have been accurately
aligned and re... | computer science |
34,474 | Monaural Multi-Talker Speech Recognition using Factorial Speech
Processing Models | cs.CL | A Pascal challenge entitled monaural multi-talker speech recognition was
developed, targeting the problem of robust automatic speech recognition against
speech like noises which significantly degrades the performance of automatic
speech recognition systems. In this challenge, two competing speakers say a
simple command... | computer science |
34,475 | Divide-and-Conquer based Ensemble to Spot Emotions in Speech using MFCC
and Random Forest | cs.SD | Besides spoken words, speech signals also carry information about speaker
gender, age, and emotional state which can be used in a variety of speech
analysis applications. In this paper, a divide and conquer strategy for
ensemble classification has been proposed to recognize emotions in speech.
Intrinsic hierarchy in em... | computer science |
34,476 | Comparative study of LSA vs Word2vec embeddings in small corpora: a case
study in dreams database | cs.CL | Word embeddings have been extensively studied in large text datasets.
However, only a few studies analyze semantic representations of small corpora,
particularly relevant in single-person text production studies. In the present
paper, we compare Skip-gram and LSA capabilities in this scenario, and we test
both techniqu... | computer science |
34,477 | Summarizing Situational and Topical Information During Crises | cs.SI | The use of microblogging platforms such as Twitter during crises has become
widespread. More importantly, information disseminated by affected people
contains useful information like reports of missing and found people, requests
for urgent needs etc. For rapid crisis response, humanitarian organizations
look for situat... | computer science |
34,478 | Automatic Detection of Small Groups of Persons, Influential Members,
Relations and Hierarchy in Written Conversations Using Fuzzy Logic | cs.CL | Nowadays a lot of data is collected in online forums. One of the key tasks is
to determine the social structure of these online groups, for example the
identification of subgroups within a larger group. We will approach the
grouping of individual as a classification problem. The classifier will be
based on fuzzy logic.... | computer science |
34,479 | A Robust Framework for Classifying Evolving Document Streams in an
Expert-Machine-Crowd Setting | cs.CL | An emerging challenge in the online classification of social media data
streams is to keep the categories used for classification up-to-date. In this
paper, we propose an innovative framework based on an Expert-Machine-Crowd
(EMC) triad to help categorize items by continuously identifying novel concepts
in heterogeneou... | computer science |
34,480 | Mining the Web for Pharmacovigilance: the Case Study of Duloxetine and
Venlafaxine | cs.CL | Adverse reactions caused by drugs following their release into the market are
among the leading causes of death in many countries. The rapid growth of
electronically available health related information, and the ability to process
large volumes of them automatically, using natural language processing (NLP)
and machine ... | computer science |
34,481 | Emergence of linguistic laws in human voice | cs.CL | Linguistic laws constitute one of the quantitative cornerstones of modern
cognitive sciences and have been routinely investigated in written corpora, or
in the equivalent transcription of oral corpora. This means that inferences of
statistical patterns of language in acoustics are biased by the arbitrary,
language-depe... | computer science |
34,482 | Investigation of Synthetic Speech Detection Using Frame- and
Segment-Specific Importance Weighting | cs.SD | Speaker verification systems are vulnerable to spoofing attacks which
presents a major problem in their real-life deployment. To date, most of the
proposed synthetic speech detectors (SSDs) have weighted the importance of
different segments of speech equally. However, different attack methods have
different strengths a... | computer science |
34,483 | Correlation-Based Method for Sentiment Classification | cs.CL | The classic supervised classification algorithms are efficient, but
time-consuming, complicated and not interpretable, which makes it difficult to
analyze their results that limits the possibility to improve them based on real
observations. In this paper, we propose a new and a simple classifier to
predict a sentiment ... | computer science |
34,484 | Semi-supervised Discovery of Informative Tweets During the Emerging
Disasters | cs.CL | The first objective towards the effective use of microblogging services such
as Twitter for situational awareness during the emerging disasters is discovery
of the disaster-related postings. Given the wide range of possible disasters,
using a pre-selected set of disaster-related keywords for the discovery is
suboptimal... | computer science |
34,485 | Dialogue Session Segmentation by Embedding-Enhanced TextTiling | cs.CL | In human-computer conversation systems, the context of a user-issued
utterance is particularly important because it provides useful background
information of the conversation. However, it is unwise to track all previous
utterances in the current session as not all of them are equally important. In
this paper, we addres... | computer science |
34,486 | A Comprehensive Comparative Study of Word and Sentence Similarity
Measures | cs.IR | Sentence similarity is considered the basis of many natural language tasks
such as information retrieval, question answering and text summarization. The
semantic meaning between compared text fragments is based on the words semantic
features and their relationships. This article reviews a set of word and
sentence simil... | computer science |
34,487 | Term-Class-Max-Support (TCMS): A Simple Text Document Categorization
Approach Using Term-Class Relevance Measure | cs.IR | In this paper, a simple text categorization method using term-class relevance
measures is proposed. Initially, text documents are processed to extract
significant terms present in them. For every term extracted from a document, we
compute its importance in preserving the content of a class through a novel
term-weightin... | computer science |
34,488 | The infochemical core | cs.CL | Vocalizations and less often gestures have been the object of linguistic
research over decades. However, the development of a general theory of
communication with human language as a particular case requires a clear
understanding of the organization of communication through other means.
Infochemicals are chemical compo... | computer science |
34,489 | Dis-S2V: Discourse Informed Sen2Vec | cs.CL | Vector representation of sentences is important for many text processing
tasks that involve clustering, classifying, or ranking sentences. Recently,
distributed representation of sentences learned by neural models from unlabeled
data has been shown to outperform the traditional bag-of-words representation.
However, mos... | computer science |
34,490 | Modeling Ambiguity, Subjectivity, and Diverging Viewpoints in Opinion
Question Answering Systems | cs.IR | Product review websites provide an incredible lens into the wide variety of
opinions and experiences of different people, and play a critical role in
helping users discover products that match their personal needs and
preferences. To help address questions that can't easily be answered by reading
others' reviews, some ... | computer science |
34,491 | Text Segmentation using Named Entity Recognition and Co-reference
Resolution in English and Greek Texts | cs.CL | In this paper we examine the benefit of performing named entity recognition
(NER) and co-reference resolution to an English and a Greek corpus used for
text segmentation. The aim here is to examine whether the combination of text
segmentation and information extraction can be beneficial for the
identification of the va... | computer science |
34,492 | Sentiment Analysis of Review Datasets Using Naive Bayes and K-NN
Classifier | cs.IR | The advent of Web 2.0 has led to an increase in the amount of sentimental
content available in the Web. Such content is often found in social media web
sites in the form of movie or product reviews, user comments, testimonials,
messages in discussion forums etc. Timely discovery of the sentimental or
opinionated web co... | computer science |
34,493 | CBAS: context based arabic stemmer | cs.CL | Arabic morphology encapsulates many valuable features such as word root.
Arabic roots are being utilized for many tasks; the process of extracting a
word root is referred to as stemming. Stemming is an essential part of most
Natural Language Processing tasks, especially for derivative languages such as
Arabic. However,... | computer science |
34,494 | Measuring Asymmetric Opinions on Online Social Interrelationship with
Language and Network Features | cs.SI | Instead of studying the properties of social relationship from an objective
view, in this paper, we focus on individuals' subjective and asymmetric
opinions on their interrelationships. Inspired by the theories from
sociolinguistics, we investigate two individuals' opinions on their
interrelationship with their interac... | computer science |
34,495 | Structure vs. Language: Investigating the Multi-factors of Asymmetric
Opinions on Online Social Interrelationship with a Case Study | cs.SI | Though current researches often study the properties of online social
relationship from an objective view, we also need to understand individuals'
subjective opinions on their interrelationships in social computing studies.
Inspired by the theories from sociolinguistics, the latest work indicates that
interactive langu... | computer science |
34,496 | Domain Adaptation For Formant Estimation Using Deep Learning | cs.CL | In this paper we present a domain adaptation technique for formant estimation
using a deep network. We first train a deep learning network on a small read
speech dataset. We then freeze the parameters of the trained network and use
several different datasets to train an adaptation layer that makes the obtained
network ... | computer science |
34,497 | Truth Discovery with Memory Network | cs.CL | Truth discovery is to resolve conflicts and find the truth from
multiple-source statements. Conventional methods mostly research based on the
mutual effect between the reliability of sources and the credibility of
statements, however, pay no attention to the mutual effect among the
credibility of statements about the s... | computer science |
34,498 | Automatic recognition of child speech for robotic applications in noisy
environments | cs.CL | Automatic speech recognition (ASR) allows a natural and intuitive interface
for robotic educational applications for children. However there are a number
of challenges to overcome to allow such an interface to operate robustly in
realistic settings, including the intrinsic difficulties of recognising child
speech and h... | computer science |
34,499 | An Automated System for Essay Scoring of Online Exams in Arabic based on
Stemming Techniques and Levenshtein Edit Operations | cs.IR | In this article, an automated system is proposed for essay scoring in Arabic
language for online exams based on stemming techniques and Levenshtein edit
operations. An online exam has been developed on the proposed mechanisms,
exploiting the capabilities of light and heavy stemming. The implemented online
grading syste... | computer science |
34,500 | Increasing the throughput of machine translation systems using clouds | cs.CL | The manuscript presents an experiment at implementation of a Machine
Translation system in a MapReduce model. The empirical evaluation was done
using fully implemented translation systems embedded into the MapReduce
programming model. Two machine translation paradigms were studied: shallow
transfer Rule Based Machine T... | computer science |
34,501 | Getting Started with Neural Models for Semantic Matching in Web Search | cs.IR | The vocabulary mismatch problem is a long-standing problem in information
retrieval. Semantic matching holds the promise of solving the problem. Recent
advances in language technology have given rise to unsupervised neural models
for learning representations of words as well as bigger textual units. Such
representation... | computer science |
34,502 | Landmark-based consonant voicing detection on multilingual corpora | cs.CL | This paper tests the hypothesis that distinctive feature classifiers anchored
at phonetic landmarks can be transferred cross-lingually without loss of
accuracy. Three consonant voicing classifiers were developed: (1) manually
selected acoustic features anchored at a phonetic landmark, (2) MFCCs (either
averaged across ... | computer science |
34,503 | Generalized Entropies and the Similarity of Texts | cs.CL | We show how generalized Gibbs-Shannon entropies can provide new insights on
the statistical properties of texts. The universal distribution of word
frequencies (Zipf's law) implies that the generalized entropies, computed at
the word level, are dominated by words in a specific range of frequencies. Here
we show that th... | computer science |
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