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Machine Translation systems are models which aim to translate text from one language into another. There are multiple ways of building such a model (Rule Based, Data driven, Hybrid etc.). In this system description paper, we use data driven techniques to build MT systems. As the name suggests, data driven MT systems ma... | 0 |
It is a common tendency among multilingual people who are non-native English speakers to code-mix in their speech using English-based phonetic typing. This linguistic phenomenon, particularly in social media like Twitter 2 , poses a great challenge to the conventional Natural Language Processing (NLP) study area.Within... | 0 |
The problem of grammar recognition is a decision problem of determining whether a string belongs to a language induced by a grammar. For context-free grammars (CFGs), recognition can be done using parsing algorithms such as the CKY algorithm (Kasami 1965; Younger 1967; Cocke and Schwartz 1970) or the Earley algorithm (... | 0 |
Terminological processing has long been recognised as one of the crucial aspects of systematic knowledge acquisition and of many NLP applications (IR, IE, corpus querying, etc.) . However, term variation has been under-discussed and is rarely accounted for in such applications.When naming a new concept, scientists and ... | 0 |
This paper describes how reference decisions are made in PROVERB, a system that verbalizes machine-found natural deduction (ND) proofs. A piece of argumentative text such as the proof of a mathematical theorem can be viewed as a sequence of derivations. Each such derivation is called a proof communicative act (PCA), fo... | 0 |
The detection and definition of influence in social contexts is becoming increasingly popular in computational sociolinguistics and related disciplines (Eisenstein et al., 2014; Nguyen et al., 2016; Cork et al., 2020) , mainly due to the availability of data from large-scale social media that allow us to study an unpre... | 0 |
Embodied conversation enables a speaker to refer to non-linguistic entities in the surrounding situation, using little to no descriptive content. Models of non-linguistic context dependence tend to focus on a fairly well-defined set of expressions, with their reference to entities in the non-linguistic context governed... | 0 |
Semantic Text Similarity (STS) plays an important role in many Natural language processing tasks, such as Question Answering (Narayanan and Harabagiu, 2004) , Machine Translation (Beale et al., 1995) , Automatic Summarization (Wang et al., 2008) and Word Sense Disambiguation (Navigli and Velardi, 2005) . Since STS is a... | 0 |
Prepositional phrase (PP) attachment disambiguation, the task of identifying the correct attachment site for each preposition in the syntax tree, has often been described as the canonical case of structural ambiguity in NLP, with crucial impact on semantic interpretation. What makes PP attachment such a challenging tas... | 0 |
The generative end-to-end dialog model (GEDM) is one of the most powerful methods of learning dialog agents from raw conversational data in both chat-oriented and task-oriented domains (Serban et al., 2016; Wen et al., 2016; Zhao et al., 2017) . Its base model is an encoder-decoder network (Cho et al., 2014) that uses ... | 0 |
Nous nous intéressons dans cet article à l'interprétation des GN définis, indéfinis et quantifiés notamment lorsqu'ils se trouvent dans la portée d'un autre GN, comme dans les exemples suivants :(1) a. Les invités ont trouvé un chat. b. Au moins la moitié des profs pense qu'aucun étudiant ne parle deux des langues étud... | 0 |
Extraction of event argument information at a document level is an important non-trivial task that requires a system to have advanced natural language understanding capabilities. Most of the existing event-argument extraction systems (Nguyen et al., 2016; Veyseh et al., 2020) pertain to a sentence-level focus, Figure 1... | 0 |
In an increasingly globalized world, non-native speakers and writers all over the world produce a huge amount of second language (L2) data every day. There is naturally a need to automatically annotate such large-scale atypical data with rich lexical, syntactic, semantic and even pragmatic information. High-performance... | 0 |
Natural language provides a variety of devices for expressing relations between elements in a text.. Simply positioning two sentences in sequence conveys an implicit relation between them:(1) I bought a book. I'm going to read it on the plane.Clauses may also be joined with explicit lexical connectives:(2) I bought a b... | 0 |
Information-retrieval-based (IR-based) QA systems typically employ a search engine and a passage retrieval module that narrows down the answer search space from a huge corpus to a small set of sentences. On the contrary, QA systems depending on reading comprehension are provided with a passage for answer extraction. In... | 0 |
The 2020 Social Media Mining for Health Applications Workshop (Klein et al., 2020) launched several natural language processing tasks using social media mining for health monitoring for automatic classification of tweets: that mention medications, multilingual tweets that report adverse effects, tweets reporting a birt... | 0 |
Most researches on automatic paraphrasing aim either at document modification for a wide range of NLP applications (Shirai et al., 1998; Tomuro and Lytinen, 2001) , at reading comprehension support (Inui and Yamamoto, 2001 ), or at transformation based on external constraints (Dras, 1998) . On the other hand, authoring... | 0 |
Movie and TV subtitles constitute a prime resource for the compilation of parallel corpora. From a linguistic perspective, subtitles cover a wide and interesting breadth of genres, from colloquial language or slang to narrative and expository discourse (as in e.g. documentaries). Large databases of subtitles are also a... | 0 |
Over the last few years, 'temporality' has drawn a significant attention to the community of Natural Language Processing (NLP) and Information Retrieval (IR). Time is an intrinsic property that aids in ordering events in a sequential order from the past to present to future. This ordering of events is very crucial in a... | 0 |
Sentiment analysis (SA) deals with automatic detection of opinion orientation in text (Liu and others, 2010) . Domainspecificity of sentiment words, and, as a result, sentiment analysis is also a well-known challenge. A popular example being 'unpredictable' that is positive for a book review (as in 'The plot of the boo... | 0 |
Plain text parallel corpora are relatively widely available and widely used in NLP, such as machine translation system development (Koehn, 2005, e.g., ) . In contrast, there are very few parallel sense tagged corpora due to the expense of tagging the corpora and creating the sense inventories in multiple languages. The... | 0 |
Conditional random fields (CRFs; Lafferty et al, 2001 ) and other conditional log-linear models (Berger et al., 1996) achieve strong performance for many NLP problems, but the conditional loglikelihood (CLL) criterion optimized when training these models cannot take a task-specific cost function into account.In this pa... | 0 |
La comparaison des caractéristiques prosodiques des langues romanes a fait l'objet de plusieurs études depuis quelque dix ou quinze ans. Le projet AMPER par exemple (Contini et al., 2002) décrit les différences prosodiques de phrases comparables dans de nombreuses variétés de langues romanes. Plus récemment, dans un ou... | 0 |
Many language applications have involved deep learning techniques to learn text representation through neural models (Bengio et al., 2003; Mikolov et al., 2013; Devlin et al., 2019) , performing composition over the learned representation for downstream tasks (Collobert et al., 2011; Socher et al., 2013) . However, the... | 0 |
Named entity recognition (NER) aims to identify and classify entities in a text into predefined types, which is an essential tool for information extraction. It has also been proven to be useful in various downstream natural language processing (NLP) tasks, including information retrieval (Banerjee et al., 2019) , ques... | 0 |
Modern spoken dialogue systems -such as Intelligent Personal Digital Assistants (IPDAs) like Google Assistant, Siri, and Alexa -provide users a natural language interface to help complete tasks such as reserving restaurants, checking the weather, playing music etc. Spoken language understanding (SLU) is a central compo... | 0 |
Abusive and offensive content such as aggression, cyberbulling, and hate speech have become pervasive in social media. The widespread of offensive content in social media is a reason of concern for governments worldwide and technology companies, which have been heavily investing in ways to cope with such content using ... | 0 |
"Evidence Based Medicine (EBM) is the conscientious, explicit, and judicious use of current best evidence in making decisions about the care of individual patients" (Sackett et al., 1996) . EBM requires to identify the best evidence, understand the methodology and strength of the approaches reported in the evidence, an... | 0 |
With the rapidly increasing biomedical literature, text mining has become popular for finding biomedical information in text. Among others, named entity recognition (NER) for bio-entities such as genes and proteins is a fundamental task because extracting biological relationships begins with entity identification. Howe... | 0 |
This paper gives an overview of a new examplebased generation technique that is designed to make grammar-based generation easier to deploy in dialogue systems. Dialogue systems present several specific requirements for a practical generation component. First, the generator needs to be fast enough to support real-time i... | 0 |
Human disease is "a disorder of structure or function in a human that produces specific signs or symptoms" (Oxford-English-Dictionary, 2020). Disease is one of the fundamental biological entities in biomedical research and consequently it is frequently searched for in the scientific literature (Islamaj Dogan et al., 20... | 0 |
Dependency parsing is a crucial component of many natural language processing (NLP) systems for tasks such as relation extraction (Bunescu and Mooney, 2005) , statistical machine translation (Xu et al., 2009) , text classification (Özgür and Güngör, 2010) , and question answering (Cui et al., 2005) . Supervised approac... | 0 |
Participants in the BLGNLP2017 shared task were invited to either build sentiment analysis systems (as a Builder team) or break them, by compiling linguistically motivated test cases that result in false predictions (as a Breaker team). A data set of movie reviews was provided as the domain for participating systems an... | 0 |
The idea of using logic as a conceptual framework in question-answering systems is not new. The fact that it can formally deal with the notion of logical consequence makes it particularly attractive for representing meaning. Standard predicate calculus, however, does not seem adequate for representing all the semantic ... | 0 |
The EmoContext task in the Semantic Evaluation 2019 (SemEval 2019) competition focuses on the classification of textual dialogues i.e. a user short conversation with a bot, into 'happy', 'sad', 'angry' and 'others' sentiment classes. Understanding emotions in textual conversations is a challenging task mainly because o... | 0 |
There has long been a shared belief among English for academic or specific purposes (EAP and ESP) instructors that it is necessary to provide students with a list of academic vocabulary 1 irrespective of their specialized domain(s). There are two main reasons why academic vocabulary receives so much attention in EAP in... | 0 |
To build an expressive Text-To-Speech (TTS) system able to read books of different literary genres, using various discourse modes and speaking styles, a corpus that covers all these specificities is required. Usually, corpora built for TTS purposes are less than ten hours long and monospeaker. In addition, the content ... | 0 |
In this paper, we provide a conceptual basis for thinking of machine translation in terms of synchronous grammars in general, and probabilistic synchronous tree-adjoining grammars in particular. The basis is conceptual in that the arguments are based on generalizations about the translation relation at a conceptual lev... | 0 |
Intelligent Tutoring Systems (ITSs) help students master a certain topic. Research on the next generation of ITSs (Evens et al., 1993; Rosé and Freedman, 2000; Aleven, 2001; Graesser et al., 2001 ) explores NL as one of the keys to bridge the gap between current ITSs and human tutors (Anderson et al., 1995) .Our work i... | 0 |
The flow of inference between communicative intentions and domain information is often essential to discourse processing. It is well reflected in this discourse from Moore and Pollack (1992) :(1)a. George Bush supports big business. b. He's sure to veto House Bill 1711.There are at least three different interpretations... | 0 |
In the past, paraphrases have come under the scrutiny of many research communities. Information retrieval researchers have used paraphrasing techniques for query reformulation in order to increase the recall of information retrieval engines (Sparck Jones and Tait, 1984) . Natural language generation researchers have us... | 0 |
Recent research in coreference resolution -the problem of determining which noun phrases (NPs) in a text or dialogue refer to which real-world entity -has exhibited a shift from knowledgebased approaches to data-driven approaches, yielding learning-based coreference systems that rival their hand-crafted counterparts in... | 0 |
Research in Cross-Language Information Retrieval (CLIR) has a long history, resulting in the formation of evaluation venues such as CLEF [CLEF, undated] and NTCIR [NTCIR, undated] . European and Oriental languages received the initial focus, but in recent years the CLEF evaluation has included Indian languages [Jagarla... | 0 |
Since the beginning of systematic research in second language acquisition (SLA) in the 1970s, one line of investigation was to identify and analyze stages of development that learners pass through when acquiring a second or a foreign language. See Sharwood-Smith and Truscott (2005) for a re-cent discussion. Stage ident... | 0 |
In many Natural Language Processing (NLP) tasks we find that a large collection of manuallyannotated text is used to train and test supervised machine learning models. While these models have been shown to perform very well when tested on the text collection related to the training data (what we call the source domain)... | 0 |
Social media platforms, such as Twitter and Facebook, have gained more and more popularity in recent years. One reason is their promise of free speech, which also obviously has its drawbacks. With the rise of social media, hate speech has spread on these platforms as well (Duggan, 2017) . But hate speech is not a pure ... | 0 |
The newly intensive use of machine learning techniques as well as the need of evaluation data has led Natural Language Processing (NLP) to develop large annotated corpora. The interest for such enriched language resources has reached domains (semantics, pragmatics, affective computing) where the annotation process is h... | 0 |
A lot of information in natural language is of a causal nature: relations between events, explanations, argumentations are all important to the understanding of texts, and thus useful in question-answering (Oh et al., 2013) , information extraction (Khoo et al., 2000; nan Cao et al., 2014) or textual entailment (Gordon... | 0 |
When a review or a social media post talks about a product or service, the user might want to discuss multiple aspects or sub-topics related to the product or service being discussed. For example, in a restaurant review, while the customer might have good things to say about the food quality offered at a restaurant, sh... | 0 |
There is a significant research effort at Educational Testing Service (ETS) directed at the development of techniques for the automatic generation of test items in various types of assessment, including mathematics, verbal, and analytical reasoning applications. The potential benefits of such automatic item generation ... | 0 |
Ariane-G5 is a generator of machine translation systems developed and improved by the GETA group 1 during the years 1970 and 1980. This framework, despite the numerous publications and cooperative projects that made it widely known, remains of difficult access because of the "mainframe" environment under which it runs ... | 0 |
Auslan Signbank 1 is an on-line dictionary for Australian Sign Language (Auslan) and is the latest in a long series of lexical resources for Auslan developed by Trevor Johnson and others. Beginning with a Filemaker Pro database (Johnston, 2001) , the Auslan lexical database has been developed as a resource to inform th... | 0 |
This paper presents the results of the shared tasks of the joint Workshop on statistical Machine Translation (WMT) and Metrics for MAchine TRanslation (MetricsMATR), which was held at ACL 2010. This builds on four previous WMT workshops (Koehn and Monz, 2006; Callison-Burch et al., 2007; Callison-Burch et al., 2008; Ca... | 0 |
One of the emerging trends of natural language technologies is their use for the humanities and sciences. There is a constant increase in the production of scientific papers and experts are faced with an explosion of information that makes it difficult to have an overview of the state of the art in a given domain (Lars... | 0 |
For many low-resource languages, spoken language resources are more likely to come with translations than with transcriptions. Most of the world's languages are not written, so there is no orthography for transcription. Phonetic transcription is possible but too costly to produce at scale. Even when a minority language... | 0 |
Large-scale transformer-based language models, such as BERT (Devlin et al., 2018) , are now the state-of-the-art for a myriad of tasks in natural language processing. However, these models are well-documented to perpetuate harmful social biases, specifically by regurgitating the social biases present in their training ... | 0 |
Recently, neural networks (NNs) dominate the state-of-the-art results on a wide range of natural language processing (NLP) tasks. The commonly used neural networks in NLP include Recurrent NNs, Convolutional NNs, Recursive NNs and their combinations. NNs are known for their strong abilities to learn features automatica... | 0 |
In this paper, we present a study on the effect of context relevance decay on the entropy of linguistic signals in natural discourses. Context relevance decay refers to the phenomenon that contextual cues that are distant from an upcoming event (e.g. production of a new linguistic signal) are less likely to be relevant... | 0 |
Learning the mapping from natural language sentences to formal meaning representations has become one of the main targets in natural language processing. Recent research has focused on learning the semantic parsers directly from corpora that consist of sentences paired with their meaning representations (Artzi and Zett... | 0 |
The Karlsruhe Institute of Technology participated in the IWSLT 2014 Evaluation Campaign with systems for English→German, German→English and English→French, covering all official directions, as well as English→Chinese and English→Arabic. All systems were submitted for the machine translation (MT) track, with additional... | 0 |
Automatic email to-do generation is the task of summarizing to-do items from given emails (Mukherjee et al., 2020) to help people overview overwhelming numbers of emails they receive every day (Radicati and Hoang, 2011) and schedule their daily work. Unlike prior research on emails such as generating email conversation... | 0 |
A substantial body of work has investigated contemporary language models (LMs) by assessing whether their behavior is consistent with the rules of syntax Marvin and Linzen, 2018; Warstadt et al., 2020) . 1 Among other structures, these studies have investigated agreement (Linzen et al., 2016; Gulordava et al., 2018) 1 ... | 0 |
Large-scale comparable corpora are available in many language pairs and are viewed as a source of valuable information for multilingual applications. Identifying translation correspondences in this type of corpora permits to construct bilingual lexicons for low-resourced languages, and to complement and reduce the spar... | 0 |
The goal of this work is to become able to automatically acquire hyponymy relations for a wide range of words or phrases from HTML documents on the WWW. We do not use particular lexicosyntactic patterns, as previous attempts have (Hearst, 1992; Caraballo, 1999; Imasumi, 2001; Fleischman et al., 2003; Morin and Jacquemi... | 0 |
The development of computational tutorial dialogue systems has become more and more prevalent (Aleven and Rose, 2003) , as one method of attempting to close the performance gap between human and computer tutors. While many such systems have yielded successful evaluations with students, most are currently text-based (Ev... | 0 |
The democratization of books on digital tablets has allowed the design of new methods to support people with reading troubles. Children's book publishers have thus proposed adaptations for young readers, with the use of specific typefaces, larger margins and text spaces, or refined illustrations to help them to better ... | 0 |
Learned word representations are widely used in NLP tasks such as tagging, named entity recognition, and parsing (Miller et al., 2004; Koo et al., 2008; Turian et al., 2010; Täckström et al., 2012; Huang et al., 2014; Bansal et al., 2014) . The idea in such representations is that words with similar context have simila... | 0 |
In a natural language, words interact among themselves in different ways -some words co-occur with certain words at a very high probability than other words. These co-occurrences are nontrivial, as in their patterns cannot be inferred from the frequency distribution of the individual words. Understanding the structure ... | 0 |
Text summarization is an NLP task with many real-world applications. The ever-increasing amount of unstructured information in text form calls for methods to automatically extract the relevant information from documents and present it in condensed form. Within the field of summarization, different paradigms are recogni... | 0 |
The task of fine-grained entity typing (FET) is to assign a semantic label to a span in a text. The task is distinct from coarse-grained entity typing as done by named entity recognition systems because these systems are restricted to a small set of labels like 'person', 'organization' and 'location' which are not help... | 0 |
Distributed word representation (i.e., word embedding) is a technique that represents words as continuous vectors, which is an important research topic in natural language processing (NLP) (Hinton et al., 1986; Turney et al., 2010) . In recent years, it has been widely used in various NLP tasks, including neural langua... | 0 |
Peer review of writing is a commonly recommended technique to include in good writing instruction. It not only provides more feedback compared to what students might get from their instructors, but also provides opportunities for students to practice writing helpful reviews. While existing web-based peerreview systems ... | 0 |
The linear model of Statistical Machine Translation (SMT) (Och and Ney, 2002) casts translation as a search for translation hypotheses under a linear combination of weighted features: a source language sentence f is translated aŝ e(f ; w) = argmax e {wh(e, f )}(1)where translation scores are a linear combination of the... | 0 |
The utility of language samples to anyone with an interest in a given language is obvious: they can be valuable to linguists, language technologists and speakers of the language, among others. The World Wide Web (WWW) is vast repository of information with potentially large numbers of samples 1 of many languages, but l... | 0 |
With the availability of large number of colossal legal documents in electronic format, there is a rising need for effective information retrieval tools to assist in organizing, processing and retrieving this information and presenting them in a suitable user-friendly format. To that end, text summarization is an impor... | 0 |
An information system is a piece of software that has integrated components for organizing and analyzing data to aid decision making in an organization (Laudon and Laudon, 2015) . One of the major roles of an information system is to accumulate data, turn it into information and later transform that information into or... | 0 |
With the Internet's phenomenal growth, social media has become a platform for sharing information, opinion, feeling, expressions, and ideas. Most users enjoy the liberty to post or share contents in such virtual platforms without any legal authority intervention or moderation Mahesan, 2019, 2020a,b) . Some people misus... | 0 |
Sentiment lexicons are an essential component of many sentiment analysis tools. Because of their importance, many sentiment lexicons for the English language, as well as for other languages, have appeared over the years. The most commonly used English lexicons include SentiWordNet (Baccianella, Esuli, and Sebastiani 20... | 0 |
As discussed in a recent survey (Jauhiainen et al., 2018) and in previous work (Tiedemann and Ljubešić, 2012; Goutte et al., 2016) , discriminating between similar languages is one of the main challenges in automatic language identification. State-of-the-art n-gram-based language identification systems are able to disc... | 0 |
The purpose of this paper is to compare secondary predication constructions such as small clause complements, resultatives, and depictives in English and Korean and argue that these two typologically different languages employ different modes of satisfying the Case Filter (Chomsky 1981 ) in case of the subjects of smal... | 0 |
Spoken language translation has received more attention in recent times. Some of the notable attempts include Verbmobil (Wahlster, 2000) and Nespole (Metze et at., 2002) . Many corpora have been compiled for this purpose covering various domains, including conversations in travel and medical domains. Typically, these c... | 0 |
Code-switching (CS) is a natural extension of the language used among immigrant communities (Toribio and Bullock, 2012) . Bilingual speakers fluently switch between the language of their background culture and the language of the country they live in, by alternating inter-sentence, intrasentence, or even intra-word. Th... | 0 |
Different interests, cultural backgrounds, and socializations make people disagree on taking a certain course of action. A debate is a means for the involved parties to resolve their disagreement. A debate is characterized by a topic, e.g., "Should one legalize abortion?". Upon the topic, the disagreeing parties have a... | 0 |
Far more scientific information exists in the literature than in any structured database. Convenient access to this information could significantly benefit research activities in various fields. The emerging technology of information extraction (Appelt and Israel 1997, Hearst 1999) provides a means of gaining access to... | 0 |
to-text generation is an essential task for text generation from structured data. It aims at automatically producing descriptive natural language text to help people obtain the salient information from the tables. Over the past several years, neural text generation methods have made significant progress on this task. L... | 0 |
In applying speech recognition techniques to retrieve information from large unrestricted text corpora, several issues immediately arise. The recognition vocabulary is very large (being the same size as the corpus vocabulary). Each new corpus may cover a different domain, requiring new specialized vocabulary. Furthermo... | 0 |
Language modeling for speech recognition has focused on robustness, using statistical techniques such as n-grams, whereas work in language understanding and information extraction has relied more on rule based techniques to leverage linguistic and domain information. However, the knowledge needed in these two component... | 0 |
The language understanding (LU) module is a key component of dialogue system (DS), parsing user's utterances into corresponding semantic concepts (or semantic slots 1 ). For example, the utterance "Show me flights from Boston to New York" can be parsed into (from city=Boston, to city=New York) (Pieraccini et al., 1992)... | 0 |
Accent predicting problem refers to the situation where accents are removed (e.g. by some email preprocessing systems), cannot be entered (e.g. by standard English keyboards), or not explicitly represented in the text (e.g. in Arabic). We resolve the languages using Roman characters in writing together with additional ... | 0 |
Opinion mining (OM), which aims to find the opinion structures of "Who expressed what opinions towards what." in one sentence, has achieved much attention in recent years (Katiyar and Cardie, 2016; Marasović and Frank, 2018; Zhang et al., 2019b Zhang et al., , 2020 . The opinion analysis has many NLP applications, such... | 0 |
Hypernymy relationship plays a critical role in language understanding because it enables generalization, which lies at the core of human cognition (Yu et al. (2015) ). It has been widely used in various NLP applications (Espinosa Anke et al. (2016) ), from word sense disambiguation (Agirre et al. (2014) ) to informati... | 0 |
In a language, an idea might be expressed in an immense number of ways. This poses a serious issue for many linguistic tasks and particularly for machine translation (MT) evaluation. In automatic machine translation evaluation, outputs of an MT system are compared to a reference translation, i.e. translation provided b... | 0 |
How can we extract social meaning from speech, deciding if a speaker is particularly engaged in the conversation, is uncomfortable or awkward, or is particularly friendly and flirtatious? Understanding these meanings and how they are signaled in language is an important sociolinguistic task in itself. Extracting them a... | 0 |
A major problem in domain-specific speech recognition is the lack of sufficient in-domain data for acoustic modeling and language modeling. In the case of language modeling, one could train a n-gram based LM using a huge set of out of domain data and, then, adapt it to the domain using a given set of in-domain data and... | 0 |
Words are in general ambiguous and can have several related or unrelated meanings depending on context. For instance, the word rock can refer to both a stone and a music genre, but in the sentence "Without the guitar, there would be no rock music" the sense of rock is no longer ambiguous. The task of assigning a word t... | 0 |
South Africa has 11 official languages and since the majority of South Africans are multilingual, code-switching occurs commonly and spontaneously. Code-switching is the phenomenon of using more than one language within the same conversation or utterance (Van Dulm, 2007) . Language switches may even occur mid-word, as ... | 0 |
Recent advancements in self-supervised pretraining techniques drastically changed the way we design Natural Language Processing (NLP) systems. Even though, pretraining has been present in NLP for many years (Mikolov et al., 2013; Pennington et al., 2014; Bojanowski et al., 2017) , only recently we observed a shift from... | 0 |
Over the past few years, a growing number of researchers have begun to look at some of the fundamental questions in linguistics in a new light, using new tools and methodologies to explore a number of unresolved issues. Among these issues are questions about the origin and the evolution of natural languages -how a lang... | 0 |
Recent success of DNNs in various natural language processing (NLP) tasks has attracted attention from the research community attempting to extend their application to new tasks. Nevertheless, the large amount of labelled data required to train DNNs limits their application to new tasks and new languages because it is ... | 0 |
We present a rule-based, multilingual system for detecting monolingual binary entailment between pairs of words using Wiktionary definitions, dependency parsing, and semantic graphs. We define entailment over pairs of semantic graphs built from dictionary definitions and achieve near-perfect precision on the Semeval-20... | 0 |
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