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Parsing is a basic technique in natural language processing; however, a full parser is usually costly and slow. Recently, shallow parsing has been applied to various information processing systems [12] . Compared to the performance of full parsers, a shallow parser is much faster and the parsing result is more useful f... | 0 |
Adversarial evaluation aims at filling in the gap between potential train/test distribution mismatch and revealing how models will perform under realworld inputs containing natural or malicious noise. Recently, there has been substantial work on adversarial attacks in computer vision and NLP. Unlike vision, where one c... | 0 |
In natural language parsing, part-of-speech (POS) information is seen as crucial to resolving ambiguous relationships, yet POS tags are usually too general to encapsulate a word's syntactic behavior. It is therefore attractive to consider intermediate entities which exist at a finer level than the POS tags, and the rel... | 0 |
Natural language is full of idiomatic and metaphorical uses. However, language resources such as dictionaries and lexical knowledge bases give at best poor coverage of such phenomena. In many cases, knowledge bases will mistakenly 'recognize' a word and this can lead to more harm than good: for example, a typical mista... | 0 |
In the past few years, deep neural networks (DNNs) have achieved huge successes in many data modelling and prediction tasks, ranging from speech recognition, computer vision to natural language processing. In this paper, we are interested in applying the powerful deep learning methods to financial data modelling to pre... | 0 |
Most words in Modern Hebrew (henceforth, Hebrew) script are morphologically ambiguous. This is due to the rich morphology of the Hebrew language and the inadequacy of the common way in which Hebrew is written. Morphological disambiguation is a must for many applications, such as spellers, search engines and machine tra... | 0 |
Dans tout dialogue, les phrases elliptiques sont très nombreuses et il semble important de pouvoir les traiter correctement (Fernandez & Ginzburg, 2002) . Ceci est particulièrement vrai avec MedSLT, un système de traduction automatique de la parole dans le domaine médical. Celuici traduit des questions de diagnostic po... | 0 |
The recent success of neural NLP is partially but largely due to the development of word embedding techniques (Goldberg, 2017) . Although a considerable number of studies have been made on training word embeddings from distributional information of language (Mikolov et al., 2013; Pennington et al., 2014; Bojanowski et ... | 0 |
Recently, neural network based sentence modeling approaches have been increasingly focused on for their ability to minimize the efforts in feature engineering, such as Neural Bag-of-Words (NBoW), Recurrent Neural Network (RNN) (Mikolov et al., 2010) , Recursive Neural Network (RecNN) (Pollack, 1990; Socher et al., 2013... | 0 |
This paper is a description of the system presented by the LIG laboratory to the IWSLT08 speech translation evaluation. The LIG only participated in the Arabic to English speech translation task. For translation, we used a statistical phrase-based system developed using the moses open source decoder. Section 2 of this ... | 0 |
Combinatory Categorial Grammar (CCG, Steedman (2000) ) is a prominent categorial grammar framework. Having a strong degree of lexicalism (Baldridge and Kruijff, 2003) , its grammars are encoded in terms of lexicons; that is, each lexicon is assigned with syntactic categories which dictate the syntactic derivation. One ... | 0 |
GF (Grammatical Framework (Ranta, 2011) ) is a formalism for multilingual grammars. Similarly to UD (Universal Dependencies, (Nivre et al., 2016) ), GF uses shared syntactic descriptions for multiple languages. In GF, this is achieved by using abstract syntax trees, similar to the internal representations used in compi... | 0 |
Forms of Japanese referring expressions are mainly divided into four types: bare NPs, demonstrative NPs (i.e. either as determiner or as pronoun) and zero pronouns. Out of the four types of the referring expressions, bare NPs are the most common type as a subsequent mention and zero pronouns are used only in limited co... | 0 |
Automatic language identification (LID) is the process of determining the language identity corresponding to a spoken query. It is an important technology in many applications, such as spoken language translation, multilingual speech recognition [Ma et al. 2002] , and spoken document retrieval [Dai et al. 2003 ]. In th... | 0 |
Deep Neural Network models (DNNs) now dominate the NLP literature. However, the immense progress comes with some issues. Often the research is not reproducible. Sometimes the code is not open source. Other times, available implementations fail to match the reported performance. When training DNNs, even simple baselines... | 0 |
When developing a second or foreign language (L2) course, setting vocabulary goals for learners remains a challenging task. Second language acquisition (SLA) research has shown that a reader has to know 95-98% of the running words in a text to understand it correctly (Laufer and Ravenhorst-Kalovski, 2010) . Such studie... | 0 |
Response-based learning describes a range of statistical learning methods that replace the fullinformation supervised learning scenario by extracting supervision signals from the response of an extrinsic environment to a predicted translation. Learning proceeds by "trying out" or "grounding" translations in a task that... | 0 |
The recent success and proliferation of statistical machine translation (MT) systems raise a number of important questions. Prominent among these are how to evaluate the quality of such a system efficiently and how to detect the output of such systems (for example, to avoid using it circularly as input for refining MT ... | 0 |
Relational Triple Extraction is an essential task in Information Extraction for Natural Language Processing (NLP) and Knowledge Graph (KG) , which is aimed at detecting a pair of entities along with their relation from unstructured text. For instance, there is a sentence "Paris is known as the romantic capital of Franc... | 0 |
Treebanks play a crucial role in developing parsers as well as investigating other linguistic phenomena. Which is why there has been a targeted effort to create treebanks in several languages. Some such notable efforts include the Penn treebank (Marcus et al., 1993) , the Prague Dependency treebank (Hajičová, 1998) . A... | 0 |
Knowledge discovery in the rapidly growing area of biomedicine is very important. While most knowledge are provided in a vast amount of texts, it is impossible to grasp all of the huge amount of knowledge provided in the form of natural language. Recently, computational text analysis techniques based on NLP have receiv... | 0 |
Nowadays, social networks have become one of the main means of messages spread. Shared information usually consists of different types of content. In this sense, we can find publications of videos, images, texts or audios. Memes are examples of posts that usually combine image and text. Daily the number of memes on pop... | 0 |
The detection of model robustness has been attracting increasing attention in recent years, given that deep neural networks (DNNs) of high accuracy can still be vulnerable to carefully crafted adversarial examples (Li et al., 2020) , distribution shift (Miller et al., 2020) , data transformation (Xing et al., 2020) , a... | 0 |
Typical neural text generation is observed suffering from the problems of repetitions in word ngrams, producing monotonous language, and generating short common sentences (Li et al., 2017) . To solve these problems, some researchers branch out into the way of post-editing (could be under some guidance, say sentiment po... | 0 |
The purpose of automatic text simplification (Saggion, 2017) is to provide a new version of documents that are easier to understand by a given population (Son et al., 2008; Paetzold & Specia, 2016b; Chen et al., 2016; Arya et al., 2011; Leroy et al., 2013) or easier to process by NLP applications (Chandrasekar & Sriniv... | 0 |
The last decade has seen tremendous progress in the subregular analysis of phonology and morphology (see Chandlee 2017, Heinz 2018 and references therein) . The subregular program is concerned with identifying proper subclasses of the regular languages that are sufficiently powerful for natural language, and to convert... | 0 |
Ten years ago, published the Graph-Based Algorithm (GBA) for referring expression generation (REG). REG has since become one of the most researched areas within Natural Language Generation, due in a large part to the central role it plays in communication: referring allows humans and language generation systems alike t... | 0 |
This paper addresses large-scale multi-class text classification tasks: categorizing articles in the Reuters news corpus (RCV1) according to topic and to industry sectors. A topic is a broad news category, e.g., "Economics," "Sport," "Health." A sector defines a narrower business area, e.g., "Banking," "Telecommunicati... | 0 |
We often self-disclose, that is, share our emotions, personal information, and secrets, with our friends, family, coworkers, and even strangers. Social psychologists say that the degree of self-disclosure in a relationship depends on the strength of the relationship, and strategic self-disclosure can strengthen the rel... | 0 |
The explosion of social media services like Twitter, Google+ and Facebook have led to a growing application potential for personalization in human computer systems such as personalized intelligent user interfaces, recommendation systems, and targeted advertising. Researchers have started mining these massive volumes of... | 0 |
Neural machine translation has emerged as the most promising machine translation approach in recent years, showing superior performance on public benchmarks and rapid adoption in deployments by, e.g., Google (Wu et al., 2016) , Systran (Crego et al., 2016) , and WIPO (Junczys-Dowmunt et al., 2016) . But there have also... | 0 |
The most popular frameworks (TAG, CG, LFG, HPSG) for symbolic parsing are based on the notion of grammar. They defined a set of initial structures (often strongly linked to a lexicon) and a set of rules to express how initial structures can combine into larger ones. In this setting, parsing consists in searching for a ... | 0 |
The world's written languages collectively represent hundreds of different writing systems. Transliteration is the process of converting a word's written representation in one language to its equivalent in a target language and is a key component of machine translation and cross-lingual information extraction and retri... | 0 |
With smart home technologies becoming increasingly widespread, for example in elderly care (Morris et al., 2013; Hendrich et al., 2014; Cavallo et al., 2014; Aubergé et al., 2014) , new opportunities for the collection of interaction data arise. Such environments thereby promise a dense web of functionalities and servi... | 0 |
We present work on induction of alignment rules for etymological data, in a project that studies genetic relationships among the Uralic language family. This is a continuation of previous work, reported in (Wettig and Yangarber, 2011) , where the methods were introduced. In this paper, we extend the models reported ear... | 0 |
La reconnaissance des noms propres français est un problème qui se pose dans les différents domaines du traitement automatique de la langue naturelle (TALN) : veille technologique, indexation de textes ou traduction (Daille & Morin, 2000) . Cette reconnaissance a été convenablement réalisée en extraction d'information ... | 0 |
Neural machine translation (NMT) based on the encoder-decoder framework (Sutskever et al., 2014; Luong et al., 2015b) has obtained state-of-the-art performance on many language pairs (Wu et al., 2019; . Various neural architectures have been explored for modeling NMT under this framework, such as recurrent neural netwo... | 0 |
Until now, research in the field of automatic question answering (QA) has focused on factoid (closed-class) questions like who, what, where and when questions. Results reported for the QA track of the Text Retrieval Conference (TREC) show that these types of wh-questions can be handled rather successfully (Voorhees 200... | 0 |
We participate in the WMT21 triangular machine translation task, using the direct and indirect parallel data to improve Russian-to-Chinese machine translation. The provided data consists of one noisy web corpus (Russian-Chinese, direct translation) and two combined bitexts from several public resources (English-Chinese... | 0 |
With the proliferation of information in unstructured and semi-structured form, text understanding (TU) is becoming a fundamental building block in enterprise applications. Numerous tools, algorithms and APIs have been developed to address various text understanding sub-tasks, ranging from low-level text tasks (e.g., t... | 0 |
The centering model (Grosz et al., 1995) has evolved as a major methodology for computational discourse analysis. It provides simple, yet powerful data structures, constraints and rules for the local coherence of discourse. As far as anaphora resolution is concerned, e.g., the model requires to consider those discourse... | 0 |
The Universal Dependencies (UD) project (Nivre et al., 2016) sets itself apart from previous multilingual parsing initiatives such as the CoNLL (Buchholz and Marsi, 2006; Nivre et al., 2007) and SPMRL (Seddah et al., 2013 (Seddah et al., , 2014 shared tasks with two key principles: (i) the POS tags, morphological prope... | 0 |
During the last ten years, research has been driven and products have been developed to provide efficient linguistic tools for many languages. For example, Unicode is more and more a reality in today's operating systems and Microsoft Office XP contains proofing tools for more than 40 languages. However, for most of the... | 0 |
Modeling relationships among several types of information, such as nodes in information network, has attracted great interests in natural language processing (NLP) and data mining (DM), since their modeling can uncover hidden information in data. Topic models such as authortopic model (Rosen-Zvi et al., 2004) have been... | 0 |
Graph-based (McDonald et al., 2005; McDonald and Pereira, 2006; Carreras et al., 2006) and transition-based (Yamada and Matsumoto, 2003; Nivre et al., 2006) parsing algorithms offer two different approaches to data-driven dependency parsing. Given an input sentence, a graph-based algorithm finds the highest scoring par... | 0 |
The Hidden Markov Model (HMM) [Rabiner et al. 1993 ] has been used successfully for acoustic modeling in many speech recognition systems. Given the state sequence, feature vectors are assumed to be conditionally independent, and the task of extracting the trajectory can be elegantly achieved by applying the Viterbi alg... | 0 |
Terminology is a key factor in translators' work. The development of specialized fields has grown hand in hand with advancements in science and technology. These market demands explain why translators are calling for resources to satisfy their terminological needs quickly and effectively [1] .Dictionary creation cannot... | 0 |
Relation extraction (RE) aims at extracting relational facts between entities from text, e.g., extracting the fact (SpaceX, founded by, Elon Musk) from the sentence in Figure 1 . Utilizing the structured knowledge captured by RE, we can construct or complete knowledge graphs (KGs), and eventually support downstream app... | 0 |
As collaborations across countries is the norm in the modern workplace, videoconferencing is an indispensable part of our working lives. The recent widespread adoption of remote work has necessitated effective online communication tools, especially among people who speak different languages. In this work, we present Me... | 0 |
Synonyms acquisition has mainly concerned single word terms (SWTs) using a variety of approaches such as: lexicon-based approaches (Blondel and Senellart, 2002) , multilingual approaches (Wu and Zhou, 2003; van der Plas and Tiedemann, 2006; Andrade et al., 2013) , distributional approaches (Lin, 1998; Hagiwara, 2008) ,... | 0 |
In both Hebrew and in Arabic, modern written texts are composed in script that leaves out most of the vowels of the words. Because many words that have different vowel patterns may appear identical in a vowel-less setting, considerable ambiguity exists at the word level.In Hebrew, Levinger et al. (1995) computed that 5... | 0 |
Coping with paraphrases appears to be an essential subtask in Recognizing Textual Entailment (RTE). Most RTE systems incorporate some form of lexical paraphrasing, usually relying on WordNet to identify synonym, hypernym and hyponym relations among word pairs from text and hypothesis (Bar-Haim et al., 2006, Table 2 ). ... | 0 |
Keyphrases are words or phrases that capture important concepts of a document. The task of keyphrase extraction, i.e., automatically extracting a collection of keyphrases from a document, has attracted considerable attention from the research community due to its pivotal importance in various applications like text doc... | 0 |
Kumārajīva was a monk from Kucha (龜茲 Qiūcí in Chinese), the current Aksu Prefecture in China.He started to translate the Buddhist scriptures into Chinese when he arrived in Chang'an (the presentday Xi'an), China, in 401 CE and the translation activity lasted till his death in 409 CE. With the assistance of his translat... | 0 |
Statistics show that between 1997 and 2009 the number of ELLs enrolled in U.S. public schools has increased by 51% (National Clearinghouse for Language Acquisition, 2011). ELLs who have lower literacy skills, and who are reading below grade level may be mainstreamed into regular content-area classrooms, and may not rec... | 0 |
Relation Extraction (RE) is an important aspect of information extraction that aims to discover the semantic relationships between two entity mentions appearing in the same sentence. Previous research on RE has followed either the kernelbased approach (Zelenko et al., 2003; Bunescu and Mooney, 2005; Zhao and Grishman, ... | 0 |
Neural machine translation (NMT) generally adopts an encoder-decoder framework (Kalchbrenner and Blunsom, 2013; Cho et al., 2014; Sutskever et al., 2014) , where the encoder summarizes the source sentence into a source context vector, and the decoder generates the target sentence word-by-word based on the given source.... | 0 |
Knowledge Base Question Answering (KBQA) (Xu et al., 2016) ), a task that tests the ability of a machine to understand knowledge like a human, is a challenging, central, and popular task in natural language processing. KBQA is the problem of predicting an answer for a factoid question over a given knowledge base (KB) c... | 0 |
The availability of terminological resources is crucial for experts in different fields; for instance, translators can integrate standard terminology in Term Base eXchange (TBX) format into their Computer-Aided Translation (CAT) tools, terminologists and linguists can reuse termbases in authoring tool, Natural Language... | 0 |
Part-of-speech tagging for a large corpus is a labor intensive and time-consuming task. Most of time and labors were spent on proofreading and never achieved 100% accuracy, as exemplified by many public available corpora. Since manual proofreading is inevitable, how do we derive the most cost-effective tagging algorith... | 0 |
The automated detection of plagiarism has been widely studied in the domain of written student essays, and several online services exist for this purpose. 1 In addition, there has been a series of shared tasks using common data sets of written language to compare the performance of a variety of approaches to plagiarism... | 0 |
Humans have long wanted to talk with the machine and have them comprehend and generate natural language. The task of chit-chat dialogue response generation can be described as one of the major goals in natural language processing. As such, there has been considerable interest in the sub-field of open-domain dialogue mo... | 0 |
Machine Comprehension of natural language text is a fundamental challenge in AI and it has received significant attention throughout the history of AI (Greene, 1959; McCarthy, 1976; Reiter, 1976; Winograd, 1980) . In particular, in natural language processing (NLP) it has been studied under various settings, such as mu... | 0 |
Word embeddings-representations of words which reflect semantic and syntactic information carried by them are ubiquitous in Natural Language Processing. Static word representation models such as GLOVE (Pennington et al., 2014) , CBOW, SKIPGRAM (Mikolov et al., 2013) and SENT2VEC (Pagliardini et al., 2018) obtain stand-... | 0 |
Corpora form the backbone of language technology. However corpora usually need to be annotated with structural information describing, for example, syntax or phonology. Query languages are necessary to extract useful information from these massive data sets. Moreover, annotated corpora require thousands of hours of man... | 0 |
Knowledge transfer is ubiquitous in machine learning because of the general scarcity of annotated data (Pratt, 1993; Caruana, 1997; Ruder, 2019, inter alia) . A prominent example thereof is transfer from resource-rich languages to resource-poor languages (Wu and Dredze, 2019; Ponti et al., 2019b; . Recently, Model-Agno... | 0 |
Syntactic parsing -grounded in a wide variety of formalisms (Taylor et al., 2003; De Marneffe et al., 2006; Hockenmaier and Steedman, 2007; Nivre et al., 2016 , inter alia) -has been the backbone of natural language processing (NLP) for decades, and an indispensable preprocessing step for tackling higher-level language... | 0 |
In context-aware computing, location is a fundamental component that supports a wide-range of applications (Hazas et al., 2004; Licht et al., 2017) . During natural disasters, location is crucial for situational awareness during disaster response (Son et al., 2008) . When available, targeted streams of social media dat... | 0 |
Currently, the workflow of many translation agencies include a final reviewing or proofreading process 1 where the translators' work is checked for correctness, consistency and appropriate writing style. If the translation quality is good enough, only a small amount of changes would be necessary to reach a high-quality... | 0 |
Relation extraction is to detect and classify various predefined semantic relations between two entities from text and can be very useful in many NLP applications such as question answering, e.g. to answer the query "Who is the president of the United States?", and information retrieval, e.g. to expand the query "Georg... | 0 |
Multilingual word embeddings have attracted a lot of attention in recent times. In addition to having a direct application in inherently crosslingual tasks like machine translation (Zou et al., 2013) and crosslingual entity linking (Tsai and Roth, 2016) , they provide an excellent mechanism for transfer learning, where... | 0 |
Disclaimer: Due to the nature of this research, we provide examples that contain adult language. We follow academic norms to present them in an appropriate form, however the discretion of the reader is cautioned.In recent years, Twitter has become one of the most popular social media platforms in the Arab region . On a... | 0 |
With the advent and rapidly increasing adoption of electronic interaction platforms, the communication patterns of modern societies have changed fundamentally. We observe an unprecedented upsurge of digitally transmitted private communication and exploding volumes of so-called usergenerated contents (UGC). As a major c... | 0 |
Building on the success of SemEval-2015 Task 3 "Answer Selection in Community Question Answering" 1 , we run an extension in 2016, which covers a full task on Community Question Answering (CQA) and which is, therefore, closer to the real application needs. All the information related to the task, data, participants, re... | 0 |
Words can be grouped into equivalence classes to reduce data sparsity and generalize data. Word clusters are useful in many NLP applications. Within machine translation, word classes are used in word alignment (Brown et al., 1993; Och and Ney, 2000) , translation models (Koehn and Hoang, 2007; Wuebker et al., 2013) , r... | 0 |
La traduction des documents 6crits a fait de r6els progr6s pendant ces derni6res ann6es. Nous pouvons constater l'6mergence de nouveaux syst~mes de traduction de textes qui proposent une traduction soign6e en diff~rentes langues [1] . I1 semble envisageable de les adapter pour la traduction de l'oral, ~ condition d'en ... | 0 |
The rapidly growing appearance rate of biomedical publications has increased interest in applying natural language processing (NLP) and machine learning (ML) technologies to navigate the massive volumes of biomedical literature. In particular, the use of text annotation to better automate knowledge extraction and ident... | 0 |
Lorsque les humains résolvent une anaphore, et ils sont amenés à le faire fréquemment, car c'est un phénomène massif en langue, ils font appel à de nombreuses connaissances et utilisent des heuristiques variées. Ceci a été mis en évidence par de nombreux travaux en psycholinguistique où l'influence d'une multitude de f... | 0 |
Inspired by earlier works on multimodal interfaces (e.g., Bolt, 1980; Cohen el al., 1996; Wahlster, 1991; Zancanaro et al., 1997) , we are currently building an intelligent infrastructure, called Responsive Information Architect (RIA) to aid users in their information-seeking process. Specifically, RIA engages users in... | 0 |
We present SPARSAR, a system for poetry (and text) style analysis by means of parameters derived from deep poem (and text) analysis. We use our system for deep text understanding called VENSES (XXX,2005) for that aim. SPAR-SAR(XXX,2013a) works on top of the output provided by VENSES and is organized in three main modul... | 0 |
This shared task builds on its previous seven editions to further examine automatic methods for estimating the quality of machine translation (MT) output at run-time, without the use of reference translations. It includes the (sub)tasks of wordlevel, sentence-level and document-level estimation. In addition to advancin... | 0 |
Recent years have seen considerable success in the generation of automatically obtained widecoverage deep grammars for natural language processing, given reliable and large CFG-like treebanks (for example, (Cahill et al., 2002; Guo et al., 2007; Chrupała and van Genabith, 2006) ). For research within Lexical Functional... | 0 |
The massive rise in user-generated web content, alongside with the freedom of speech in social media and anonymity of the users has brought about an increase in online offensive content and antisocial behavior. The consequences of such behavior on genuine users of the social media have become a serious concern for rese... | 0 |
Although everyone may be familiar with the notion of paraphrase in its most fundamental sense, there is still room for elaboration on how paraphrases may be automatically generated or elicited for use in language processing applications. In this survey, we make an attempt at such an elaboration. An important outcome of... | 0 |
With the exponential growth of information on the Internet, it is becoming increasingly difficult to find and organize relevant materials. Tracking task, i.e. starts from a few sample stories and finds all subsequent stories that discuss the target topic, is a new line of research to attack the problem. One of the majo... | 0 |
One of the main issues that a translator (human or machine) must address during the translation process is how to match the different word orders between the source language and the target language. Different language-pairs require different levels of word reordering. For example, when we translate between English and ... | 0 |
Time series data is ubiquitous -any measurement humans make over a period of time produces a time series. We are building a system to summarize physiological times series data such as heart rate, and blood pressure measured in neonatal intensive care units. | 0 |
The aim of text simplification (TS) is to transform given texts into their syntactically and/or lexically simpler variants which are more understandable for the target population (e.g. children, non-native speakers, people with low literacy levels, or people with various kinds of cognitive or reading impairments). It i... | 0 |
Chunk parsing (Tjong Kim Sang, 2001; Brants, 1999 ) is a simple parsing strategy both in implementation and concept. The parser first performs chunking by identifying base phrases, and convert the identified phrases to non-terminal symbols. The parser again performs chunking on the updated sequence and convert the newl... | 0 |
Relation extraction (RE), which aims to identify the semantic relation between two entities in plain text, is one of the fundamental tasks in information extraction (IE). In the deep learning era, many approaches are proposed including models based on attention mechanism (Lin et al., 2016; Zhang et al., 2017) , graph n... | 0 |
The task of relation extraction (RE) is to identify relational facts between entities from plain text, which plays an important role in large-scale knowledge graph construction. Most existing RE Figure 1 : An example from DocRED. Each document in DocRED is annotated with named entity mentions, coreference information, ... | 0 |
This paper has two aims: [i] to formulate a semantics, called Annotation-based Semantics (ABS), for the modeltheoretic interpretation of annotation structures and [ii] to recommend it as a semantics for ISO 24617 standards on semantic annotation frameworks such as ISO-TimeML (ISO, 2020) or ISO-Space (ISO, 2020) . As a ... | 0 |
Developing reading ability is an essential part of language acquisition. However, finding proper reading materials for training language learners at a specific level of proficiency is a demanding and timeconsuming task for English instructors as well as the readers themselves. To automate the process of reading materia... | 0 |
Microtexts, like SMS messages, Twitter posts, and Facebook status updates, are becoming a popular medium for real-time communication in the modern digital age. The ubiquitous nature of mobile phones, tablets, and other Internet-enabled consumer devices provide users with the ability to express what is on their mind nea... | 0 |
Systematic inequality and discrimination to women does not appear offline but also in online communication. MEME is an image characterized by a visual content with an overlaying text added MEME creators. Although most of MEMEs are created with the intention of making funny jokes, some of MEMEs are created as a form aga... | 0 |
It requires no proof that usually language users can detect lexical ambiguity in figurative speech without classifying it into types like metaphor, pun, humor, irony, sarcasm, etc. At the same time, such terminology is necessary in studyng these phenomena as well as solving problems of automatic classification. In our ... | 0 |
Pre-trained feature extractors, such as BERT (Devlin et al., 2018) for natural language processing and VGG (Simonyan and Zisserman, 2014) for computer vision, have become effective methods for improving the performance of deep learning models. In the last year, models similar to BERT have become state-of-the-art in man... | 0 |
People with mobility or physical impairments may have difficulty with touch-based user interfaces. Automatic speech recognition (ASR) potentially offers an alternative, natural means of device access, but such systems can still be challenging to use for individuals who have speech impediments or disorders. For example,... | 0 |
NLP is in a position to bring-forth scalable, costeffective solutions for promoting well-being. Such solutions can serve many segments of the population such as people living in medically underserved communities with limited access to clinicians, and people with limited mobility. These solutions can also serve those in... | 0 |
It is generally accepted that there are two main approaches for producing automatic summaries. The first one is called extract and rearrange because it extracts the most important sentences from a text and tries to arrange them in a coherent way. These methods were introduced in the late 50s (Luhn, 1958) and similar me... | 0 |
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