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9,100 | A Uniform Approach to Analogies, Synonyms, Antonyms, and Associations | cs.CL | Recognizing analogies, synonyms, antonyms, and associations appear to be four
distinct tasks, requiring distinct NLP algorithms. In the past, the four tasks
have been treated independently, using a wide variety of algorithms. These four
semantic classes, however, are a tiny sample of the full range of semantic
phenomen... | computer science |
9,101 | A Linear Classifier Based on Entity Recognition Tools and a Statistical
Approach to Method Extraction in the Protein-Protein Interaction Literature | cs.CL | We participated, in the Article Classification and the Interaction Method
subtasks (ACT and IMT, respectively) of the Protein-Protein Interaction task of
the BioCreative III Challenge. For the ACT, we pursued an extensive testing of
available Named Entity Recognition and dictionary tools, and used the most
promising on... | computer science |
9,102 | Bayesian Query-Focused Summarization | cs.CL | We present BayeSum (for ``Bayesian summarization''), a model for sentence
extraction in query-focused summarization. BayeSum leverages the common case in
which multiple documents are relevant to a single query. Using these documents
as reinforcement for query terms, BayeSum is not afflicted by the paucity of
informatio... | computer science |
9,103 | Learning Attitudes and Attributes from Multi-Aspect Reviews | cs.CL | The majority of online reviews consist of plain-text feedback together with a
single numeric score. However, there are multiple dimensions to products and
opinions, and understanding the `aspects' that contribute to users' ratings may
help us to better understand their individual preferences. For example, a
user's impr... | computer science |
9,104 | A machine-compiled macroevolutionary history of Phanerozoic life | cs.DB | Many aspects of macroevolutionary theory and our understanding of biotic
responses to global environmental change derive from literature-based
compilations of palaeontological data. Existing manually assembled databases
are, however, incomplete and difficult to assess and enhance. Here, we develop
and validate the qual... | computer science |
9,105 | Scalable Topical Phrase Mining from Text Corpora | cs.CL | While most topic modeling algorithms model text corpora with unigrams, human
interpretation often relies on inherent grouping of terms into phrases. As
such, we consider the problem of discovering topical phrases of mixed lengths.
Existing work either performs post processing to the inference results of
unigram-based t... | computer science |
9,106 | Performance Investigation of Feature Selection Methods | cs.IR | Sentiment analysis or opinion mining has become an open research domain after
proliferation of Internet and Web 2.0 social media. People express their
attitudes and opinions on social media including blogs, discussion forums,
tweets, etc. and, sentiment analysis concerns about detecting and extracting
sentiment or opin... | computer science |
9,107 | Recognizing Speech in a Novel Accent: The Motor Theory of Speech
Perception Reframed | cs.CL | The motor theory of speech perception holds that we perceive the speech of
another in terms of a motor representation of that speech. However, when we
have learned to recognize a foreign accent, it seems plausible that recognition
of a word rarely involves reconstruction of the speech gestures of the speaker
rather tha... | computer science |
9,108 | Feature Learning with Gaussian Restricted Boltzmann Machine for Robust
Speech Recognition | cs.CL | In this paper, we first present a new variant of Gaussian restricted
Boltzmann machine (GRBM) called multivariate Gaussian restricted Boltzmann
machine (MGRBM), with its definition and learning algorithm. Then we propose
using a learned GRBM or MGRBM to extract better features for robust speech
recognition. Our experim... | computer science |
9,109 | Probabilistic Cascading for Large Scale Hierarchical Classification | cs.LG | Hierarchies are frequently used for the organization of objects. Given a
hierarchy of classes, two main approaches are used, to automatically classify
new instances: flat classification and cascade classification. Flat
classification ignores the hierarchy, while cascade classification greedily
traverses the hierarchy f... | computer science |
9,110 | Solving Verbal Comprehension Questions in IQ Test by Knowledge-Powered
Word Embedding | cs.CL | Intelligence Quotient (IQ) Test is a set of standardized questions designed
to evaluate human intelligence. Verbal comprehension questions appear very
frequently in IQ tests, which measure human's verbal ability including the
understanding of the words with multiple senses, the synonyms and antonyms, and
the analogies ... | computer science |
9,111 | Semi-supervised and Unsupervised Methods for Categorizing Posts in Web
Discussion Forums | cs.CL | Web discussion forums are used by millions of people worldwide to share
information belonging to a variety of domains such as automotive vehicles,
pets, sports, etc. They typically contain posts that fall into different
categories such as problem, solution, feedback, spam, etc. Automatic
identification of these categor... | computer science |
9,112 | Sentence Level Recurrent Topic Model: Letting Topics Speak for
Themselves | cs.LG | We propose Sentence Level Recurrent Topic Model (SLRTM), a new topic model
that assumes the generation of each word within a sentence to depend on both
the topic of the sentence and the whole history of its preceding words in the
sentence. Different from conventional topic models that largely ignore the
sequential orde... | computer science |
9,113 | A Joint Model of Language and Perception for Grounded Attribute Learning | cs.CL | As robots become more ubiquitous and capable, it becomes ever more important
to enable untrained users to easily interact with them. Recently, this has led
to study of the language grounding problem, where the goal is to extract
representations of the meanings of natural language tied to perception and
actuation in the... | computer science |
9,114 | Cross Language Text Classification via Subspace Co-Regularized
Multi-View Learning | cs.CL | In many multilingual text classification problems, the documents in different
languages often share the same set of categories. To reduce the labeling cost
of training a classification model for each individual language, it is
important to transfer the label knowledge gained from one language to another
language by con... | computer science |
9,115 | Fast and accurate sentiment classification using an enhanced Naive Bayes
model | cs.CL | We have explored different methods of improving the accuracy of a Naive Bayes
classifier for sentiment analysis. We observed that a combination of methods
like negation handling, word n-grams and feature selection by mutual
information results in a significant improvement in accuracy. This implies that
a highly accurat... | computer science |
9,116 | A Subband-Based SVM Front-End for Robust ASR | cs.CL | This work proposes a novel support vector machine (SVM) based robust
automatic speech recognition (ASR) front-end that operates on an ensemble of
the subband components of high-dimensional acoustic waveforms. The key issues
of selecting the appropriate SVM kernels for classification in frequency
subbands and the combin... | computer science |
9,117 | Complex Question Answering: Unsupervised Learning Approaches and
Experiments | cs.CL | Complex questions that require inferencing and synthesizing information from
multiple documents can be seen as a kind of topic-oriented, informative
multi-document summarization where the goal is to produce a single text as a
compressed version of a set of documents with a minimum loss of relevant
information. In this ... | computer science |
9,118 | Content Modeling Using Latent Permutations | cs.IR | We present a novel Bayesian topic model for learning discourse-level document
structure. Our model leverages insights from discourse theory to constrain
latent topic assignments in a way that reflects the underlying organization of
document topics. We propose a global model in which both topic selection and
ordering ar... | computer science |
9,119 | Which Clustering Do You Want? Inducing Your Ideal Clustering with
Minimal Feedback | cs.IR | While traditional research on text clustering has largely focused on grouping
documents by topic, it is conceivable that a user may want to cluster documents
along other dimensions, such as the authors mood, gender, age, or sentiment.
Without knowing the users intention, a clustering algorithm will only group
documents... | computer science |
9,120 | Performance Evaluation of Machine Learning Classifiers in Sentiment
Mining | cs.LG | In recent years, the use of machine learning classifiers is of great value in
solving a variety of problems in text classification. Sentiment mining is a
kind of text classification in which, messages are classified according to
sentiment orientation such as positive or negative. This paper extends the idea
of evaluati... | computer science |
9,121 | Improving Collaborative Filtering based Recommenders using Topic
Modelling | cs.IR | Standard Collaborative Filtering (CF) algorithms make use of interactions
between users and items in the form of implicit or explicit ratings alone for
generating recommendations. Similarity among users or items is calculated
purely based on rating overlap in this case,without considering explicit
properties of users o... | computer science |
9,122 | Inducing Language Networks from Continuous Space Word Representations | cs.LG | Recent advancements in unsupervised feature learning have developed powerful
latent representations of words. However, it is still not clear what makes one
representation better than another and how we can learn the ideal
representation. Understanding the structure of latent spaces attained is key to
any future advance... | computer science |
9,123 | Scalable and Robust Construction of Topical Hierarchies | cs.LG | Automated generation of high-quality topical hierarchies for a text
collection is a dream problem in knowledge engineering with many valuable
applications. In this paper a scalable and robust algorithm is proposed for
constructing a hierarchy of topics from a text collection. We divide and
conquer the problem using a t... | computer science |
9,124 | Evaluating topic coherence measures | cs.LG | Topic models extract representative word sets - called topics - from word
counts in documents without requiring any semantic annotations. Topics are not
guaranteed to be well interpretable, therefore, coherence measures have been
proposed to distinguish between good and bad topics. Studies of topic coherence
so far are... | computer science |
9,125 | Using Local Alignments for Relation Recognition | cs.CL | This paper discusses the problem of marrying structural similarity with
semantic relatedness for Information Extraction from text. Aiming at accurate
recognition of relations, we introduce local alignment kernels and explore
various possibilities of using them for this task. We give a definition of a
local alignment (L... | computer science |
9,126 | Incremental Knowledge Base Construction Using DeepDive | cs.DB | Populating a database with unstructured information is a long-standing
problem in industry and research that encompasses problems of extraction,
cleaning, and integration. Recent names used for this problem include dealing
with dark data and knowledge base construction (KBC). In this work, we describe
DeepDive, a syste... | computer science |
9,127 | Ordering-sensitive and Semantic-aware Topic Modeling | cs.LG | Topic modeling of textual corpora is an important and challenging problem. In
most previous work, the "bag-of-words" assumption is usually made which ignores
the ordering of words. This assumption simplifies the computation, but it
unrealistically loses the ordering information and the semantic of words in the
context.... | computer science |
9,128 | On the Effects of Low-Quality Training Data on Information Extraction
from Clinical Reports | cs.LG | In the last five years there has been a flurry of work on information
extraction from clinical documents, i.e., on algorithms capable of extracting,
from the informal and unstructured texts that are generated during everyday
clinical practice, mentions of concepts relevant to such practice. Most of this
literature is a... | computer science |
9,129 | Author Name Disambiguation by Using Deep Neural Network | cs.DL | Author name ambiguity decreases the quality and reliability of information
retrieved from digital libraries. Existing methods have tried to solve this
problem by predefining a feature set based on expert's knowledge for a specific
dataset. In this paper, we propose a new approach which uses deep neural
network to learn... | computer science |
9,130 | LSHTC: A Benchmark for Large-Scale Text Classification | cs.IR | LSHTC is a series of challenges which aims to assess the performance of
classification systems in large-scale classification in a a large number of
classes (up to hundreds of thousands). This paper describes the dataset that
have been released along the LSHTC series. The paper details the construction
of the datsets an... | computer science |
9,131 | Information Extraction with Character-level Neural Networks and Free
Noisy Supervision | cs.CL | We present an architecture for information extraction from text that augments
an existing parser with a character-level neural network. The network is
trained using a measure of consistency of extracted data with existing
databases as a form of noisy supervision. Our architecture combines the ability
of constraint-base... | computer science |
9,132 | Incorporating Language Level Information into Acoustic Models | cs.CL | This paper proposed a class of novel Deep Recurrent Neural Networks which can
incorporate language-level information into acoustic models. For simplicity, we
named these networks Recurrent Deep Language Networks (RDLNs). Multiple
variants of RDLNs were considered, including two kinds of context information,
two methods... | computer science |
9,133 | Empirical Evaluation of Four Tensor Decomposition Algorithms | cs.LG | Higher-order tensor decompositions are analogous to the familiar Singular
Value Decomposition (SVD), but they transcend the limitations of matrices
(second-order tensors). SVD is a powerful tool that has achieved impressive
results in information retrieval, collaborative filtering, computational
linguistics, computatio... | computer science |
9,134 | From Frequency to Meaning: Vector Space Models of Semantics | cs.CL | Computers understand very little of the meaning of human language. This
profoundly limits our ability to give instructions to computers, the ability of
computers to explain their actions to us, and the ability of computers to
analyse and process text. Vector space models (VSMs) of semantics are beginning
to address the... | computer science |
9,135 | Local Space-Time Smoothing for Version Controlled Documents | cs.GR | Unlike static documents, version controlled documents are continuously edited
by one or more authors. Such collaborative revision process makes traditional
modeling and visualization techniques inappropriate. In this paper we propose a
new representation based on local space-time smoothing that captures important
revis... | computer science |
9,136 | WebSets: Extracting Sets of Entities from the Web Using Unsupervised
Information Extraction | cs.LG | We describe a open-domain information extraction method for extracting
concept-instance pairs from an HTML corpus. Most earlier approaches to this
problem rely on combining clusters of distributionally similar terms and
concept-instance pairs obtained with Hearst patterns. In contrast, our method
relies on a novel appr... | computer science |
9,137 | Connecting Language and Knowledge Bases with Embedding Models for
Relation Extraction | cs.CL | This paper proposes a novel approach for relation extraction from free text
which is trained to jointly use information from the text and from existing
knowledge. Our model is based on two scoring functions that operate by learning
low-dimensional embeddings of words and of entities and relationships from a
knowledge b... | computer science |
9,138 | Visualizing Bags of Vectors | cs.IR | The motivation of this work is two-fold - a) to compare between two different
modes of visualizing data that exists in a bag of vectors format b) to propose
a theoretical model that supports a new mode of visualizing data. Visualizing
high dimensional data can be achieved using Minimum Volume Embedding, but the
data ha... | computer science |
9,139 | Text Classification For Authorship Attribution Analysis | cs.DL | Authorship attribution mainly deals with undecided authorship of literary
texts. Authorship attribution is useful in resolving issues like uncertain
authorship, recognize authorship of unknown texts, spot plagiarism so on.
Statistical methods can be used to set apart the approach of an author
numerically. The basic met... | computer science |
9,140 | Category-Theoretic Quantitative Compositional Distributional Models of
Natural Language Semantics | cs.CL | This thesis is about the problem of compositionality in distributional
semantics. Distributional semantics presupposes that the meanings of words are
a function of their occurrences in textual contexts. It models words as
distributions over these contexts and represents them as vectors in high
dimensional spaces. The p... | computer science |
9,141 | Subjectivity Classification using Machine Learning Techniques for Mining
Feature-Opinion Pairs from Web Opinion Sources | cs.IR | Due to flourish of the Web 2.0, web opinion sources are rapidly emerging
containing precious information useful for both customers and manufactures.
Recently, feature based opinion mining techniques are gaining momentum in which
customer reviews are processed automatically for mining product features and
user opinions ... | computer science |
9,142 | On the Ground Validation of Online Diagnosis with Twitter and Medical
Records | cs.SI | Social media has been considered as a data source for tracking disease.
However, most analyses are based on models that prioritize strong correlation
with population-level disease rates over determining whether or not specific
individual users are actually sick. Taking a different approach, we develop a
novel system fo... | computer science |
9,143 | How Many Topics? Stability Analysis for Topic Models | cs.LG | Topic modeling refers to the task of discovering the underlying thematic
structure in a text corpus, where the output is commonly presented as a report
of the top terms appearing in each topic. Despite the diversity of topic
modeling algorithms that have been proposed, a common challenge in successfully
applying these ... | computer science |
9,144 | Feature Engineering for Knowledge Base Construction | cs.DB | Knowledge base construction (KBC) is the process of populating a knowledge
base, i.e., a relational database together with inference rules, with
information extracted from documents and structured sources. KBC blurs the
distinction between two traditional database problems, information extraction
and information integr... | computer science |
9,145 | Interpretable Low-Rank Document Representations with Label-Dependent
Sparsity Patterns | cs.CL | In context of document classification, where in a corpus of documents their
label tags are readily known, an opportunity lies in utilizing label
information to learn document representation spaces with better discriminative
properties. To this end, in this paper application of a Variational Bayesian
Supervised Nonnegat... | computer science |
9,146 | "Look Ma, No Hands!" A Parameter-Free Topic Model | cs.LG | It has always been a burden to the users of statistical topic models to
predetermine the right number of topics, which is a key parameter of most topic
models. Conventionally, automatic selection of this parameter is done through
either statistical model selection (e.g., cross-validation, AIC, or BIC) or
Bayesian nonpa... | computer science |
9,147 | Statistically Significant Detection of Linguistic Change | cs.CL | We propose a new computational approach for tracking and detecting
statistically significant linguistic shifts in the meaning and usage of words.
Such linguistic shifts are especially prevalent on the Internet, where the
rapid exchange of ideas can quickly change a word's meaning. Our meta-analysis
approach constructs ... | computer science |
9,148 | Integer-Programming Ensemble of Temporal-Relations Classifiers | cs.CL | The extraction of temporal events from text and understanding temporal
relations between the events are major challenges in natural language
processing. We present an ensemble method, which reconciles the output of
multiple classifiers of temporal expressions, subject to consistency
constraints across the output. Compu... | computer science |
9,149 | Weakly Supervised Multi-Embeddings Learning of Acoustic Models | cs.SD | We trained a Siamese network with multi-task same/different information on a
speech dataset, and found that it was possible to share a network for both
tasks without a loss in performance. The first task was to discriminate between
two same or different words, and the second was to discriminate between two
same or diff... | computer science |
9,150 | Extraction of Salient Sentences from Labelled Documents | cs.CL | We present a hierarchical convolutional document model with an architecture
designed to support introspection of the document structure. Using this model,
we show how to use visualisation techniques from the computer vision literature
to identify and extract topic-relevant sentences.
We also introduce a new scalable ... | computer science |
9,151 | Measuring academic influence: Not all citations are equal | cs.DL | The importance of a research article is routinely measured by counting how
many times it has been cited. However, treating all citations with equal weight
ignores the wide variety of functions that citations perform. We want to
automatically identify the subset of references in a bibliography that have a
central academ... | computer science |
9,152 | Classifying Tweet Level Judgements of Rumours in Social Media | cs.SI | Social media is a rich source of rumours and corresponding community
reactions. Rumours reflect different characteristics, some shared and some
individual. We formulate the problem of classifying tweet level judgements of
rumours as a supervised learning task. Both supervised and unsupervised domain
adaptation are cons... | computer science |
9,153 | Learning Contextualized Semantics from Co-occurring Terms via a Siamese
Architecture | cs.IR | One of the biggest challenges in Multimedia information retrieval and
understanding is to bridge the semantic gap by properly modeling concept
semantics in context. The presence of out of vocabulary (OOV) concepts
exacerbates this difficulty. To address the semantic gap issues, we formulate a
problem on learning contex... | computer science |
9,154 | LCSTS: A Large Scale Chinese Short Text Summarization Dataset | cs.CL | Automatic text summarization is widely regarded as the highly difficult
problem, partially because of the lack of large text summarization data set.
Due to the great challenge of constructing the large scale summaries for full
text, in this paper, we introduce a large corpus of Chinese short text
summarization dataset ... | computer science |
9,155 | Answer Sequence Learning with Neural Networks for Answer Selection in
Community Question Answering | cs.CL | In this paper, the answer selection problem in community question answering
(CQA) is regarded as an answer sequence labeling task, and a novel approach is
proposed based on the recurrent architecture for this problem. Our approach
applies convolution neural networks (CNNs) to learning the joint representation
of questi... | computer science |
9,156 | Exploratory topic modeling with distributional semantics | cs.IR | As we continue to collect and store textual data in a multitude of domains,
we are regularly confronted with material whose largely unknown thematic
structure we want to uncover. With unsupervised, exploratory analysis, no prior
knowledge about the content is required and highly open-ended tasks can be
supported. In th... | computer science |
9,157 | The Polylingual Labeled Topic Model | cs.CL | In this paper, we present the Polylingual Labeled Topic Model, a model which
combines the characteristics of the existing Polylingual Topic Model and
Labeled LDA. The model accounts for multiple languages with separate topic
distributions for each language while restricting the permitted topics of a
document to a set o... | computer science |
9,158 | Incremental Active Opinion Learning Over a Stream of Opinionated
Documents | cs.IR | Applications that learn from opinionated documents, like tweets or product
reviews, face two challenges. First, the opinionated documents constitute an
evolving stream, where both the author's attitude and the vocabulary itself may
change. Second, labels of documents are scarce and labels of words are
unreliable, becau... | computer science |
9,159 | Sampled Weighted Min-Hashing for Large-Scale Topic Mining | cs.LG | We present Sampled Weighted Min-Hashing (SWMH), a randomized approach to
automatically mine topics from large-scale corpora. SWMH generates multiple
random partitions of the corpus vocabulary based on term co-occurrence and
agglomerates highly overlapping inter-partition cells to produce the mined
topics. While other a... | computer science |
9,160 | Data-selective Transfer Learning for Multi-Domain Speech Recognition | cs.LG | Negative transfer in training of acoustic models for automatic speech
recognition has been reported in several contexts such as domain change or
speaker characteristics. This paper proposes a novel technique to overcome
negative transfer by efficient selection of speech data for acoustic model
training. Here data is ch... | computer science |
9,161 | Improved Twitter Sentiment Prediction through Cluster-then-Predict Model | cs.IR | Over the past decade humans have experienced exponential growth in the use of
online resources, in particular social media and microblogging websites such as
Facebook, Twitter, YouTube and also mobile applications such as WhatsApp, Line,
etc. Many companies have identified these resources as a rich mine of marketing
kn... | computer science |
9,162 | Multi-GPU Distributed Parallel Bayesian Differential Topic Modelling | cs.CL | There is an explosion of data, documents, and other content, and people
require tools to analyze and interpret these, tools to turn the content into
information and knowledge. Topic modeling have been developed to solve these
problems. Topic models such as LDA [Blei et. al. 2003] allow salient patterns
in data to be ex... | computer science |
9,163 | Freshman or Fresher? Quantifying the Geographic Variation of Internet
Language | cs.CL | We present a new computational technique to detect and analyze statistically
significant geographic variation in language. Our meta-analysis approach
captures statistical properties of word usage across geographical regions and
uses statistical methods to identify significant changes specific to regions.
While previous... | computer science |
9,164 | Fast Latent Variable Models for Inference and Visualization on Mobile
Devices | cs.LG | In this project we outline Vedalia, a high performance distributed network
for performing inference on latent variable models in the context of Amazon
review visualization. We introduce a new model, RLDA, which extends Latent
Dirichlet Allocation (LDA) [Blei et al., 2003] for the review space by
incorporating auxiliary... | computer science |
9,165 | Distributed Deep Learning for Question Answering | cs.LG | This paper is an empirical study of the distributed deep learning for
question answering subtasks: answer selection and question classification.
Comparison studies of SGD, MSGD, ADADELTA, ADAGRAD, ADAM/ADAMAX, RMSPROP,
DOWNPOUR and EASGD/EAMSGD algorithms have been presented. Experimental results
show that the distribu... | computer science |
9,166 | Mining Local Gazetteers of Literary Chinese with CRF and Pattern based
Methods for Biographical Information in Chinese History | cs.CL | Person names and location names are essential building blocks for identifying
events and social networks in historical documents that were written in
literary Chinese. We take the lead to explore the research on algorithmically
recognizing named entities in literary Chinese for historical studies with
language-model ba... | computer science |
9,167 | Hierarchical Latent Semantic Mapping for Automated Topic Generation | cs.LG | Much of information sits in an unprecedented amount of text data. Managing
allocation of these large scale text data is an important problem for many
areas. Topic modeling performs well in this problem. The traditional generative
models (PLSA,LDA) are the state-of-the-art approaches in topic modeling and
most recent re... | computer science |
9,168 | Hierarchical classification of e-commerce related social media | cs.SI | In this paper, we attempt to classify tweets into root categories of the
Amazon browse node hierarchy using a set of tweets with browse node ID labels,
a much larger set of tweets without labels, and a set of Amazon reviews.
Examining twitter data presents unique challenges in that the samples are short
(under 140 char... | computer science |
9,169 | Aspect-based Opinion Summarization with Convolutional Neural Networks | cs.CL | This paper considers Aspect-based Opinion Summarization (AOS) of reviews on
particular products. To enable real applications, an AOS system needs to
address two core subtasks, aspect extraction and sentiment classification. Most
existing approaches to aspect extraction, which use linguistic analysis or
topic modeling, ... | computer science |
9,170 | Jointly Modeling Topics and Intents with Global Order Structure | cs.CL | Modeling document structure is of great importance for discourse analysis and
related applications. The goal of this research is to capture the document
intent structure by modeling documents as a mixture of topic words and
rhetorical words. While the topics are relatively unchanged through one
document, the rhetorical... | computer science |
9,171 | From Word Embeddings to Item Recommendation | cs.LG | Social network platforms can use the data produced by their users to serve
them better. One of the services these platforms provide is recommendation
service. Recommendation systems can predict the future preferences of users
using their past preferences. In the recommendation systems literature there
are various techn... | computer science |
9,172 | Learning Hidden Unit Contributions for Unsupervised Acoustic Model
Adaptation | cs.CL | This work presents a broad study on the adaptation of neural network acoustic
models by means of learning hidden unit contributions (LHUC) -- a method that
linearly re-combines hidden units in a speaker- or environment-dependent manner
using small amounts of unsupervised adaptation data. We also extend LHUC to a
speake... | computer science |
9,173 | A Convolutional Attention Network for Extreme Summarization of Source
Code | cs.LG | Attention mechanisms in neural networks have proved useful for problems in
which the input and output do not have fixed dimension. Often there exist
features that are locally translation invariant and would be valuable for
directing the model's attention, but previous attentional architectures are not
constructed to le... | computer science |
9,174 | Blind score normalization method for PLDA based speaker recognition | cs.CL | Probabilistic Linear Discriminant Analysis (PLDA) has become state-of-the-art
method for modeling $i$-vector space in speaker recognition task. However the
performance degradation is observed if enrollment data size differs from one
speaker to another. This paper presents a solution to such problem by
introducing new P... | computer science |
9,175 | PCA Method for Automated Detection of Mispronounced Words | cs.SD | This paper presents a method for detecting mispronunciations with the aim of
improving Computer Assisted Language Learning (CALL) tools used by foreign
language learners. The algorithm is based on Principle Component Analysis
(PCA). It is hierarchical with each successive step refining the estimate to
classify the test... | computer science |
9,176 | Personalized Speech recognition on mobile devices | cs.CL | We describe a large vocabulary speech recognition system that is accurate,
has low latency, and yet has a small enough memory and computational footprint
to run faster than real-time on a Nexus 5 Android smartphone. We employ a
quantized Long Short-Term Memory (LSTM) acoustic model trained with
connectionist temporal c... | computer science |
9,177 | Recursive Neural Conditional Random Fields for Aspect-based Sentiment
Analysis | cs.CL | In aspect-based sentiment analysis, extracting aspect terms along with the
opinions being expressed from user-generated content is one of the most
important subtasks. Previous studies have shown that exploiting connections
between aspect and opinion terms is promising for this task. In this paper, we
propose a novel jo... | computer science |
9,178 | Yelp Dataset Challenge: Review Rating Prediction | cs.CL | Review websites, such as TripAdvisor and Yelp, allow users to post online
reviews for various businesses, products and services, and have been recently
shown to have a significant influence on consumer shopping behaviour. An online
review typically consists of free-form text and a star rating out of 5. The
problem of p... | computer science |
9,179 | On a Topic Model for Sentences | cs.CL | Probabilistic topic models are generative models that describe the content of
documents by discovering the latent topics underlying them. However, the
structure of the textual input, and for instance the grouping of words in
coherent text spans such as sentences, contains much information which is
generally lost with t... | computer science |
9,180 | Source-LDA: Enhancing probabilistic topic models using prior knowledge
sources | cs.CL | A popular approach to topic modeling involves extracting co-occurring n-grams
of a corpus into semantic themes. The set of n-grams in a theme represents an
underlying topic, but most topic modeling approaches are not able to label
these sets of words with a single n-gram. Such labels are useful for topic
identification... | computer science |
9,181 | Retrieving and Ranking Similar Questions from Question-Answer Archives
Using Topic Modelling and Topic Distribution Regression | cs.IR | Presented herein is a novel model for similar question ranking within
collaborative question answer platforms. The presented approach integrates a
regression stage to relate topics derived from questions to those derived from
question-answer pairs. This helps to avoid problems caused by the differences
in vocabulary us... | computer science |
9,182 | TwiSE at SemEval-2016 Task 4: Twitter Sentiment Classification | cs.CL | This paper describes the participation of the team "TwiSE" in the SemEval
2016 challenge. Specifically, we participated in Task 4, namely "Sentiment
Analysis in Twitter" for which we implemented sentiment classification systems
for subtasks A, B, C and D. Our approach consists of two steps. In the first
step, we genera... | computer science |
9,183 | Automatic Pronunciation Generation by Utilizing a Semi-supervised Deep
Neural Networks | cs.CL | Phonemic or phonetic sub-word units are the most commonly used atomic
elements to represent speech signals in modern ASRs. However they are not the
optimal choice due to several reasons such as: large amount of effort required
to handcraft a pronunciation dictionary, pronunciation variations, human
mistakes and under-r... | computer science |
9,184 | A Novel Framework to Expedite Systematic Reviews by Automatically
Building Information Extraction Training Corpora | cs.IR | A systematic review identifies and collates various clinical studies and
compares data elements and results in order to provide an evidence based answer
for a particular clinical question. The process is manual and involves lot of
time. A tool to automate this process is lacking. The aim of this work is to
develop a fr... | computer science |
9,185 | A Curriculum Learning Method for Improved Noise Robustness in Automatic
Speech Recognition | cs.CL | The performance of automatic speech recognition systems under noisy
environments still leaves room for improvement. Speech enhancement or feature
enhancement techniques for increasing noise robustness of these systems usually
add components to the recognition system that need careful optimization. In
this work, we prop... | computer science |
9,186 | Permutation Invariant Training of Deep Models for Speaker-Independent
Multi-talker Speech Separation | cs.CL | We propose a novel deep learning model, which supports permutation invariant
training (PIT), for speaker independent multi-talker speech separation,
commonly known as the cocktail-party problem. Different from most of the prior
arts that treat speech separation as a multi-class regression problem and the
deep clusterin... | computer science |
9,187 | Temporal Topic Analysis with Endogenous and Exogenous Processes | cs.CL | We consider the problem of modeling temporal textual data taking endogenous
and exogenous processes into account. Such text documents arise in real world
applications, including job advertisements and economic news articles, which
are influenced by the fluctuations of the general economy. We propose a
hierarchical Baye... | computer science |
9,188 | Stock trend prediction using news sentiment analysis | cs.CL | Efficient Market Hypothesis is the popular theory about stock prediction.
With its failure much research has been carried in the area of prediction of
stocks. This project is about taking non quantifiable data such as financial
news articles about a company and predicting its future stock trend with news
sentiment clas... | computer science |
9,189 | World Knowledge as Indirect Supervision for Document Clustering | cs.LG | One of the key obstacles in making learning protocols realistic in
applications is the need to supervise them, a costly process that often
requires hiring domain experts. We consider the framework to use the world
knowledge as indirect supervision. World knowledge is general-purpose
knowledge, which is not designed for... | computer science |
9,190 | Syntactically Informed Text Compression with Recurrent Neural Networks | cs.LG | We present a self-contained system for constructing natural language models
for use in text compression. Our system improves upon previous neural network
based models by utilizing recent advances in syntactic parsing -- Google's
SyntaxNet -- to augment character-level recurrent neural networks. RNNs have
proven excepti... | computer science |
9,191 | Rapid Classification of Crisis-Related Data on Social Networks using
Convolutional Neural Networks | cs.CL | The role of social media, in particular microblogging platforms such as
Twitter, as a conduit for actionable and tactical information during disasters
is increasingly acknowledged. However, time-critical analysis of big crisis
data on social media streams brings challenges to machine learning techniques,
especially the... | computer science |
9,192 | Hash2Vec, Feature Hashing for Word Embeddings | cs.CL | In this paper we propose the application of feature hashing to create word
embeddings for natural language processing. Feature hashing has been used
successfully to create document vectors in related tasks like document
classification. In this work we show that feature hashing can be applied to
obtain word embeddings i... | computer science |
9,193 | An improved uncertainty decoding scheme with weighted samples for
DNN-HMM hybrid systems | cs.LG | In this paper, we advance a recently-proposed uncertainty decoding scheme for
DNN-HMM (deep neural network - hidden Markov model) hybrid systems. This
numerical sampling concept averages DNN outputs produced by a finite set of
feature samples (drawn from a probabilistic distortion model) to approximate
the posterior li... | computer science |
9,194 | Multiplex lexical networks reveal patterns in early word acquisition in
children | cs.CL | Network models of language have provided a way of linking cognitive processes
to the structure and connectivity of language. However, one shortcoming of
current approaches is focusing on only one type of linguistic relationship at a
time, missing the complex multi-relational nature of language. In this work, we
overcom... | computer science |
9,195 | Twitter Opinion Topic Model: Extracting Product Opinions from Tweets by
Leveraging Hashtags and Sentiment Lexicon | cs.CL | Aspect-based opinion mining is widely applied to review data to aggregate or
summarize opinions of a product, and the current state-of-the-art is achieved
with Latent Dirichlet Allocation (LDA)-based model. Although social media data
like tweets are laden with opinions, their "dirty" nature (as natural language)
has di... | computer science |
9,196 | Topic Modeling over Short Texts by Incorporating Word Embeddings | cs.CL | Inferring topics from the overwhelming amount of short texts becomes a
critical but challenging task for many content analysis tasks, such as content
charactering, user interest profiling, and emerging topic detecting. Existing
methods such as probabilistic latent semantic analysis (PLSA) and latent
Dirichlet allocatio... | computer science |
9,197 | Topic Browsing for Research Papers with Hierarchical Latent Tree
Analysis | cs.CL | Academic researchers often need to face with a large collection of research
papers in the literature. This problem may be even worse for postgraduate
students who are new to a field and may not know where to start. To address
this problem, we have developed an online catalog of research papers where the
papers have bee... | computer science |
9,198 | FPGA-Based Low-Power Speech Recognition with Recurrent Neural Networks | cs.CL | In this paper, a neural network based real-time speech recognition (SR)
system is developed using an FPGA for very low-power operation. The implemented
system employs two recurrent neural networks (RNNs); one is a
speech-to-character RNN for acoustic modeling (AM) and the other is for
character-level language modeling ... | computer science |
9,199 | Applications of Online Deep Learning for Crisis Response Using Social
Media Information | cs.CL | During natural or man-made disasters, humanitarian response organizations
look for useful information to support their decision-making processes. Social
media platforms such as Twitter have been considered as a vital source of
useful information for disaster response and management. Despite advances in
natural language... | computer science |
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