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This paper describes two simple hypernym extraction methods, given a list of domain terms and a large amount of text divided into documents. Task 17 of the 2015 Semeval campaign (Bordea et al., 2015) consists in structuring a flat list of preidentified domain terms into a list of hypernym pairs. Task organizers provide... | 0 |
Real-world data in healthcare refers to patient data routinely collected during clinic encounters such as visits and hospitalization. After each clinical visit, a set of codes representing diagnostic and procedural information are submitted to various regulatory agencies (Farkas and Szarvas, 2008) . The International C... | 0 |
This paper describes the NICT Kyoto submission to the WMT'21 Quality Estimation (QE) shared task. We participated in Task 3 "Critical Error Detection" involving four language pairs, namely English-Chinese, English-Czech, English-Japanese and English-German. A critical error is defined as a translation error falling int... | 0 |
Multilingual machine translation is commonplace, with high-quality commercial systems available in over 100 languages (Johnson et al., 2017) . However, translation from and into lowresource languages remains a challenge (Arivazhagan et al., 2019) . Additionally, translation from morphologically-rich languages to Englis... | 0 |
In recent years, syntactic representations based on head-modifier dependency relations between words have attracted a lot of interest (Kübler et al., 2009) . Research in dependency parsing -computational methods to predict such representations -has increased dramatically, due in large part to the availability of depend... | 0 |
The rise of deep learning models (deep neural networks [DNNs] ) has produced better prediction models for a plethora of fields, particularly for those that rely on unstructured data, such as computer vision and natural language processing (NLP) (Peters et al. 2018; Devlin et al. 2019) . In recent years, variants of the... | 0 |
Korean verbs' are typically divided into two groups: regular and irregular. Regular verbs are invariant throughout the paradigm. Irregular verbs, on the other hand, show alternations before certain suffixes. In the literature on Korean (e.g., Choy 1959; Huh 1965; Martin 1992) , the behavior of "irregular" verbs is usua... | 0 |
While post-editing of machine translation is an increasingly widespread practice, very few technological solutions exist that are aimed specifically at facilitating the work of the post-editor. This paper addresses this gap, by proposing a mechanism that automatically propagates post-editor corrections to further machi... | 0 |
The syntactic potential and semantic structure of a language's lexicon can either be encoded explicitly in a dictionary or ontology, or implicitly through annotated data. Rule-based natural-language processing (NLP) will typically rely on the former, machine-learning (ML) systems on the latter. For the semantic annotat... | 0 |
Recent progress in speech-to-text tasks such as automatic speech recognition (ASR) and speech translation (ST) has been achieved by the development and application of unsupervised speech pre-training methods (Oord et al., 2018; Schneider et al., 2019; Baevski et al., 2020; Conneau et al., 2020; Wu et al., 2020; Nguyen ... | 0 |
The segmentation of Chinese texts is a key problem in Chinese information processing. In the process of segmentation, the ambiguity processing, unknown Chinese words (not included in the lexicon) recognition (such as person names, organization names etc) are very difficult. As for those problems, many algorithms are pu... | 0 |
The concept of syntax-directed (SD) translation was originally proposed in compiling (Irons, 1961; Lewis and Stearns, 1968) , where the source program is parsed into a tree representation that guides the generation of the object code. Following Aho and Ullman (1972) , a translation, as a set of string pairs, can be spe... | 0 |
As discussed by Dorr and Voss (1993) , MT theory has not yet addressed the issues surrounding how the interlingua (IL) in machine translation should be defined or evaluated. This paper provides a framework for addressing such issues. We take the IL in machine translation to be defined implicitly in two distinct ways: (... | 0 |
At this point in research on natural language generation, it is important to select problems that will clarify what is at issue in the larger phenomena under study, while at the same time being small enough to yield principled results in a reasonable amount of time. To build on what the field has already accomplished, ... | 0 |
Pre-trained language models (PLMs) such as GPT (Radford et al., 2018) , BERT (Devlin et al., 2019) and XLNet (Yang et al., 2019) have become enormously popular and achieved great success on diverse natural language understanding tasks, such as sentiment analysis, question answering, and language inference. These models... | 0 |
The task of recognizing temporal expressions (sometimes also referred as time expressions or simply TIMEX) was first introduced in the Message Understanding Conference (MUC) in 1995. Temporal expressions were treated as a part of the Named Entity Recognition (NER) task, in which capitalized tokens in text were labeled ... | 0 |
Coreference resolution (CoRe) is the process of finding markables (noun phrases) referring to the same real world entity or concept. Until recently, most approaches tried to solve the problem by binary classification, where the probability of a pair of markables being coreferent is estimated from labeled data. Alternat... | 0 |
Sense-aware system has become central to many NLP and related intelligent systems.The core technique involved is the Word Sense Disambiguation (WSD) which can determine the proper sense of each word in varied contexts. Current WSD models rely largely on gold standard data from manual annotation that has been suffering ... | 0 |
The recent trend in medicine toward health promotion, rather than disease management, has forefronted the role of patient behavior and lifestyle choices in positive health outcomes. Socialcognitive theories of health-promotion (Maes and Karoly, 2005; Bandura, 2005) stress patient selfmonitoring of life-style choices, g... | 0 |
Dans diverses applications pour le traitement automatique des langues, il devient nécessaire de posséder un système formel pour décrire les relations sémantico-lexicales idiomatiques entre les unités lexicales d'une langue. Par relations sémantico-lexicales, nous entendons plus précisément, des relations syntagmatiques... | 0 |
Recent years have witnessed the rapid development of online e-commerce business, e.g. Amazon and eBay, which raises the need for better storing, organizing and analyzing the large amount of product records. An important task is how to effectively link product records across multiple databases or websites. This task ser... | 0 |
Suicide prevention hotlines can provide immediate care in critical times of need (Gould et al., 2012 (Gould et al., , 2013 Ramchand et al., 2016) . These hotlines are expanding services to text to meet growing demands and adapt to shifts in communication trends (Smith and Page, 2015) . Crisis helplines rely on counselo... | 0 |
Semantic role labeling is a complex task to discover patterns within sentences corresponding to semantic meaning. We believe it is hopeless to expect high levels of performance from either purely manual classifiers or purely learned classifiers. Rather, supplemental linguistic information must be used to support and co... | 0 |
Knowledge graphs, such as Freebase or YAGO, are networks which contain information about real-world entities and their semantic types, properties and relations. In recent years considerable effort has been invested into constructing these large knowledge bases in academic research, community-driven projects and industr... | 0 |
Language modeling is one of the core disciplines in natural language processing (NLP). Automatic speech recognition, machine translation, optical character recognition, and other tasks strongly depend on the language model (LM). An improvement in language modeling often leads to better performance of the whole task. Th... | 0 |
Semantic Textual Similarity (STS) is the task of assessing the degree to which two sentences are semantically similar. Within the SemEval STS shared tasks, this is measured on a scale ranging from 0 (no semantic similarity) to 5 (complete semantic similarity) (Cer et al., 2017) . Monolingual STS is an important task, f... | 0 |
Currently a large proportion of MT approaches which are readily portable to new language pairs are based on the Statistical Machine Translation (SMT) paradigm. The main obstacle to the creation of an SMT system is the requirement for parallel corpora between the Source Language (SL) and the Target Language (TL), which ... | 0 |
It is generally agreed that, in commercial contexts, machine translation (MT) output still needs to be post-edited in order to be acceptable to, and usable by, end-users. However, a number of factors have generated interest in the possibility of using raw, i.e. non post-edited, MT output. First, the quality of raw MT o... | 0 |
Over the past several years, neural network approaches have rapidly gained popularity in natural language processing (NLP) because of their impressive performance and flexible modeling capacity. Nevertheless, symbolic rules are still an indispensable tool in various industrial NLP applications. Regular expressions (RE)... | 0 |
Distributional methods for meaning similarity are based on the observation that similar words occur in similar contexts and measure similarity based on patterns of word occurrence in large corpora (Clark, 2012; Erk, 2012; Turney and Pantel, 2010) . More precisely, they represent words, or any other target linguistic el... | 0 |
Much previous work on linguistic annotation has necessarily focused on resource-rich languages, as it is these languages for which we have large corpora in need of linguistic annotation. In contrast, development of annotation schemata and methodologies to be used with language data from endangered languages has been le... | 0 |
Generally, Chinese Lexical Analysis consists of two phases; one is word segmentation and the other is part-of-speech(POS) tagging. Rule -based approach and statistic -based approach are two dominant ways in natural language processing, as well as Chinese Lexical Analysis. This paper will only focus on the later one. He... | 0 |
The language of social media text is unusual and irregular (Baldwin et al., 2013) , with misspellings, non-standard capitalisation and jargon, disfluency and fragmentation. Twitter is one of the sources of social media text most challenging for NLP (Eisenstein, 2013; Derczynski et al., 2013) .In particular, traditional... | 0 |
As a linguistic phenomenon that reverses the polarity of a statement or its property into opposite, negation is ubiquitous in human languages. Consider following sentence S1. A negative affix -n't negates the statement that mutual fund trades take effect until the market close. Negation processing has been shown critic... | 0 |
Japanese has several types of temporarily ambiguous sentences (TASs) (Inoue, 2006) . This paper focuses on the pattern 'NP-NOM [ VP NP-ACC V] NP-DAT NP-ACC V' as exemplified in (1). itta. said 'A police officer extended his thanks to a/the man who caught a criminal.'The first NP keekan-ga 'police.officer-NOM' tends to ... | 0 |
The use of machine translation (MT) in commercial translation and localisation workflows has grown exponentially in recent years. Relatively recent breakthroughs in the quality of statistical machine translation (SMT) output has led to the use of MT for assimilation (gisting) and MT for dissemination (post-edited © 2... | 0 |
Discriminative learning methods are ubiquitous in natural language processing. Discriminative taggers and chunkers have been the state-of-the-art for more than a decade (Ratnaparkhi, 1996; Sha and Pereira, 2003) . Furthermore, end-to-end systems like speech recognizers (Roark et al., 2004) and automatic translators (Oc... | 0 |
There are two ways in which one can integrate a discourse-based measure of textual saliency, such as that described above, with measures of saliency that are based on cohesion, position, similarity with the title, etc. The simplest way is to compute a probability distribution of the importance of textual units accordin... | 0 |
Current research in the field of Automatic Speech Recognition (ASR) and Machine Translation (MT) tends to focus on the language pairs that have a large amount of data available. This is because the quality of these systems is dependent on the amount and quality of the training data used. As a result, many such systems ... | 0 |
Distributional word representations, developed using large-scale training corpora, form an integral part of the modern NLP methodological paradigm. The advent of deep pre-trained neural language models such as BERT (Devlin et al., 2018) and GPT-2 (Radford et al., 2019) has led the shift towards the development of conte... | 0 |
Text clustering is a fundamental problem in text mining and information retrieval. Its task is to group similar texts together such that texts within a cluster are more similar to texts in other clusters. Usually, a text is represented as a bag-ofwords or term frequency-inverse document frequency (TF-IDF) vector, and t... | 0 |
Even as early as one of the first Blocks World natural language interaction systems, SHRDLU (Winograd, 1971) , discussions about structures and space have been viewed as the foundation for future language understanding systems dealing with more abstract and higher-level concepts.Since then, the field has advanced in th... | 0 |
Readability assessment is a classic problem in natural language processing, which attracts many researchers' attention in recent years (Todirascu et al., 2016; Schumacher et al., 2016; Cha et al., 2017) . The objective is to evaluate the readability of texts by levels or scores. The majority of recent readability asses... | 0 |
German particle verbs (PVs) are complex verb structures such as anstrahlen 'to beam/smile at' that combine a prefix particle (an) with a base verb (strahlen 'to beam'). PVs represent a type of multi-word expressions, which are generally known as a "pain in the neck for NLP" (Sag et al., 2002) . Even more, German PVs po... | 0 |
In recent years, the automatic extraction of terms from running text has become a subject of growing interest. Practical applications such as dictionary, lexicon and thesaurus construction and maintenance, automatic indexing and machine translation have fuelled this interest. Given that concerns in automatic term recog... | 0 |
Distributed word representations by neural networks (Mikolov et al., 2013a; Mikolov et al., 2013b; Pennington et al., 2014; Levy and Goldberg, 2014; Bojanowski et al., 2017) , which are one of the implementations of the distributional hypothesis (Harris, 1954) , have shown surprising effectiveness in representing seman... | 0 |
Learning representations of phrases is important for many tasks, such as semantic parsing (Socher et al., 2011) , machine translation (Ramisch et al., 2013) , and question answering (Seo et al., 2018) . While pretrained language models such as BERT (Devlin et al., 2018) have significantly pushed forward the state of th... | 0 |
Neural machine translation (NMT) (Sutskever et al., 2014; Bahdanau et al., 2015) is rapidly proving itself to be a strong competitor to other statistical machine translation methods. However, it still lags behind other statistical methods on very lowresource language pairs (Zoph et al., 2016; Koehn and Knowles, 2017) .... | 0 |
In scientific literature, scholars use citations to refer to external sources. These secondary sources are essential in comprehending the new research. Previous work has shown the importance of citations in scientific domains and indicated that citations include survey-worthy information (Siddharthan and Teufel, 2007; ... | 0 |
Knowledge graphs (KGs) are used to organize, manage, and retrieve structured information. The incompleteness of most real-world KGs has stimulated research on predicting missing relations between entities. A KG is of the form G = (E, R), where E is a set of entities and, R is a set of relation types or predicates. One ... | 0 |
Crowdsourcing plays an increasingly important role in collecting large-scale data resources in many research fields, including natural language, speech, and image processing. One of the major challenges of crowdsourcing is how to estimate the quality of data. In particular, it is difficult to control the quality of the... | 0 |
To develop human-like visual and language understanding of AI, the task of answering a question about the given visual content has been proposed, i.e., Visual Question Answering (VQA) (Antol et al., 2015) . Although the current state-of-the-art methods (Fukui et al., 2016; Cadene et al., 2019a ) can achieve good result... | 0 |
Hyper-parameter optimization has been receiving an increasingly amount of attention in the NLP and machine learning communities (Thornton et al., 2013; Komer et al., 2014; Bergstra et al., 2011; Bardenet et al., 2013; Zheng et al., 2013) . The performance of learning algorithms depend on the correct instantiations of t... | 0 |
L'attribution d'auteur est une tâche qui intéresse les chercheurs depuis le XIX e siècle (Holmes, 1994) . Elle a permis d'identifier l'auteur d'oeuvres de provenance contestée, comme les Federalist Papers (McEnery & Oakes, 2000) ; elle a aujourd'hui des applications dans des domaines comme la détection de plagiat dans ... | 0 |
Tamil is a language, predominantly spoken in Tamil Nadu, a state in Southern India, along with countries with a large Tamil speaking diaspora such as Sri Lanka, Malaysia and Singapore, to name a few. Telugu on the other hand is the official language of two Southern states in India, namely Andhra Pradesh and Telangana. ... | 0 |
Neural sequence to sequence models (Kalchbrenner and Blunsom, 2013; Sutskever et al., 2014; Bahdanau et al., 2015) are now a workhorse behind a wide variety of different natural language processing tasks such as machine translation, generation, summarization and simplification. The 2nd Workshop on Neural Machine Transl... | 0 |
Recurrent models (RNNs and more specifically LSTMs) have been used extensively across several NLP tasks such as machine translation (Sutskever et al., 2014) , language modeling (Melis et al., 2017) and question answering (Seo et al., 2016) . Natural languages involve phenomena such as hierarchical and long-distance dep... | 0 |
Most syntax-based statistical machine translation (SMT) systems typically utilize word alignments and parse trees on the source/target side to learn syntactic transformation rules from parallel data. The approach suffers from a practical problem that even one spurious (word alignment) link can prevent some desirable sy... | 0 |
Lexical simplification is the task of automatically rewriting a text by substituting words or phrases with simpler variants, while retaining its meaning and grammaticality. The goal is to make the text easier to understand for children, language learners, people with cognitive disabilities and even machines. Approaches... | 0 |
Neural machine translation (NMT) has witnessed great success during recent years (Sutskever et al., 2014; Bahdanau et al., 2014; Gehring et al., 2017; Vaswani et al., 2017) . One of the main reasons is that neural networks possess the powerful ability to model sufficient context by entangling all source words and targe... | 0 |
Natural languages are de facto living entities always subject to change and evolution. The diachronic dimension of natural language has played a pivotal role in the history of Linguistics. Understanding and explaining why a community of speakers "speak" as they do is of primary importance to access one's cultural herit... | 0 |
Detecting online abusive language in social media messages is gaining increasing attention from scholars and stakeholders, such as governments, social media platforms and citizens. The spread of online abusive content negatively affects the targeted victims, has a chilling effect on the democratic discourse on social n... | 0 |
Traditionally, statistical properties of sentence length distribution were investigated with the goal of settling disputed authorship (Mendenhall, 1887; Yule, 1939) . Simple models, such as a "monkeys and typewriters" Bernoulli process (Miller, 1957) do not fit the data well, and this problem is inherited from n-gram M... | 0 |
When creating text using word processing software on a personal computer, it is common to refer to books or documents relevant to the text, including various kinds of dictionaries and reference works. The tools used for accessing relevant information, such as CD-ROM dictionaries, text databases, and text retrieval soft... | 0 |
Fine-grained classification involves distinguishing between classes that have subtle variations among them. For example, in image classification, we can classify birds from non-birds, or attempt a more fine-grained classification of bird species (Akata et al., 2015) . In NLP, one example is sentiment analysis, where we... | 0 |
In this work, we propose a method of lexical disambiguation based on the notion of dependencies.In modern linguistics, Lucien Tesnière developed a formal and sophisticated theory with dependencies (Tesnière, 1959) . Nowadays, many current grammatical formalisms rely more or less explicitly on the notion of dependencies... | 0 |
Simultaneous Interpretation (SI) is an inherently difficult task that carries significant cognitive and attentional burdens. The role of the simultaneous interpreter is to accurately render the source speech in a given target language in a timely and precise manner. Interpreters employ a range of strategies, including ... | 0 |
Reference resolution and idiom processing have received much attention in natural language processing (NLP), but these phenomena are commonly treated in isolation of each other, and most treatments address only a single aspect of the respective overall problems. For example, much of the work on practical reference reso... | 0 |
Neural machine translation (NMT) based on the encoder-decoder architecture becomes the new state-of-the-art due to distributed representation and end-to-end learning (Cho et al., 2014; Bahdanau et al., 2015; Junczys-Dowmunt et al., 2016; Gehring et al., 2017; Vaswani et al., 2017) .However, the current NMT is a global ... | 0 |
Generally speaking, when we communicate through natural language, the literal meaning of the words is consistent with the meaning we want to express. Sarcasm is a form of linguistic expression when this "congruence" is broken (Wilson, 2006) .Due to the inherent metaphorical nature and subtle sentimental expression of t... | 0 |
We are interested in learning distributed sentence representation in an unsupervised fashion. Previously, the skip-thought model was introduced by Kiros et al. (2015) , which learns to explore the semantic continuity within adjacent sentences (Harris, 1954) as supervision for learning a generic sentence encoder. The sk... | 0 |
In recent years, there has been a surge of interest in using word vectors for modeling semantics. Mikolov et al. (2013a,b) introduced word2vec that includes the continuous bag-of-words (CBOW) model and the skip-gram model. 1 These models have been most widely used for generating word vectors to be used for word related... | 0 |
Discourse interpretation is an essential component of any dialogue system. However, most interactive systems developed to date afford users limited opportunities to express their views. The discourse interpretation mechanism described in this paper constitutes a step towards solving this problem.This research builds on... | 0 |
Spelling correction is used to suggest one or several hypothetical corrections for the assumed error once a spell checker detects some misspelling, which is typically identified when it cannot been found in a pre-compiled lexicon. In this paper, we focus on the problem of interactively correcting non-word errors (e.g. ... | 0 |
Factual and honest science communication is important for maintaining public trust in science (Nelkin, 1987; Moore, 2006) , and the "dominant link between academia and the media" are press releases about scientific articles (Sumner et al., 2014) . However, multiple studies have demonstrated that press releases have a s... | 0 |
Millions of opinions, conversations or just trivia are published each day in Twitter by users of different cultures, countries and ages. This provides an effective way to poll how people praise, complain or discuss about virtually any topic. Comprehending and analysing all this information has become a new challenge fo... | 0 |
Phrase-based systems, flat and hierarchical alike (Koehn et al., 2003; Koehn, 2004b; Koehn et al., 2007; Chiang, 2005; Chiang, 2007) , have achieved a much better translation coverage than wordbased ones (Brown et al., 1993) , but untranslated words remain a major problem in SMT. For example, according to Callison-Burc... | 0 |
The growing need by users to access information on the web in languages different from their own is fostering the research in the field of Crosslanguage Information Retrieval (CLIR) applications.Typically in state-of-the-art CLIR applications, information is searched by means of a query expressed in the user's mother t... | 0 |
Open-ended tasks such as dialogue reveal a number of issues with current neural text generation methods. In more strongly grounded tasks such as machine translation and image captioning, current encoder-decoder architectures provide strong performance, where mostly word-level decisions are often taken correctly by the ... | 0 |
Code-mixing (CM), the phenomenon of mixing words from two languages in a sentence, is getting increasingly commonplace in several bilingual communities 1 . Recently, much research has focused on training language models over codeswitched data for tasks like automatic speech recognition (ASR) (Winata et al., 2019; Gonen... | 0 |
Traditional high-stakes testing of spoken proficiency often evaluates the test-taker's ability to accomplish communicative tasks in a conversational setting. For example, learners may introduce themselves, respond to requests for information, or accomplish daily tasks in a role-play.Testing oral proficiency in this way... | 0 |
Text classification is a crucial task in natural language processing, which has many applications, such as sentiment analysis, intent identification and topic labeling [Aggarwal and Zhai, 2012; Wang and Manning, 2012a] . Recent years, many studies rely on neural networks and have shown promising performance.The success... | 0 |
In recent years, pretrained language models (PLMs) trained in a self-supervised manner like mask language modeling have achieved promising results on various natural language processing (NLP) tasks (Devlin et al., 2019; Liu et al., 2019b) , which learn general linguistic and semantic knowledge from massive general corp... | 0 |
Most work so far on natural language communication between man and machine has dealt with its literal aspects. That is. natural language interlaces have implicitly adopted the position that their user's input encodes a request for intormation of; action, and that their job is tO decode the request, retrieve the informa... | 0 |
Cross-document coreference resolution of entities and events (CDCR) is an increasingly important problem, as downstream tasks that benefit from coreference annotations -such as question answering, information extraction, and summarization -begin interpreting multiple documents simultaneously. Yet the number of candidat... | 0 |
White space serves as the word delimiter in Latin alphabet-based languages. However, in written Chinese text, there is no word delimiter. Thus, in almost all tasks of Chinese natural language processing (NLP), the first step is to segment a Chinese sentence into a sequence of words. This is the task of Chinese word seg... | 0 |
Lemmatization is the task of finding the lemma or base form for a given word token. It is used as a preprocessing step for information retrieval and other NLP applications for languages with rich morphology and has been shown to outperform stemming for some tasks (Korenius et al., 2004) . Lemmatization can be formalize... | 0 |
A semantic role in a language is a semantic relationship between a syntactic constituent and a predicate. The shared task of CoNLL-2004 relates to recognize semantic roles in English (X. Carreras, 2004) . Given a sentence, the task is to analyze a proposition expressed by a target verb of a sentence. Especially, for ea... | 0 |
Searching for the optimal parameters in linear models (Och and Ney, 2002) of Statistical Machine Translation (SMT) has been a major challenge to the MT community. The most widely used approach todate is Minimum-Error-Rate Training (MERT: (Och, 2003) ), which tries to find the parameters that optimize the translation qu... | 0 |
Although the availability of computational resources for the study of language change has experienced a considerable growth in the last decade, scholars still face considerable challenges when trying to conduct research in certain areas such as syntactic change. This is true even in the case of languages for which ther... | 0 |
Over the last few years, there has been growing interest in investigating the adversarial robustness of NLP models, including new methods for generating adversarial examples and better approaches to defending against these adversaries (Alzantot et al., 2018; Kuleshov et al., 2018; Gao et al., 2018; Ebrahimi et al., 201... | 0 |
Artificial neural networks (ANNs) are powerful computational models that are able to implicitly learn syntactic and semantic features necessary for a variety of natural language tasks. These empirical results raise a deeper scientific question: to what extent do the features learned by ANNs resemble the linguistic comp... | 0 |
Humor as a phenomenon has interested scholars from diverse fields since time immemorial (Morreall, 2012). The abundance of research studies dedicated to humor is not only due to the fascinating nature of the domain but also due to its impact in everyday life (Martin and Lefcourt, 1983) (McGee and Shevlin, 2009) . (Sack... | 0 |
One interesting and difficult subtask of sentiment analysis is the automatic recognition of so-called implicit opinions or polar facts: Statements that express a valuation yet do not include context-independent polar words that belong in standard sentiment (polarity) dictionaries. With a polar fact, an author gives a d... | 0 |
In past years, the concatenative synthesis approach has been adopted for use in many text-to-speech (TTS) systems [Hamon et al. 1989] [Iwahashi et al. 1995] [Shih et al. 1996] [Chen et al. 1998 ] [Chou et al. 1998 ] [Charpentier et al. 1986] . Concatenative synthesis uses real recorded speech segments as synthesis unit... | 0 |
To validate a scientific experiment, its reproducibility is one of the bases of the scientific process because it may be proven wrong (Popper, 2005) . As is well-known, if a repeated experiment gives different results, its validity is questioned as it fails to be generalised. The preoccupation for reproducibility when ... | 0 |
Combinatory Categorial Grammar (CCG, Steedman (2000) ) is a compositional, semantically transparent formalism that is both linguistically expressive and computationally tractable. It has been used for a variety of tasks, such as wide-coverage parsing (Hockenmaier and Steedman, 2002; Clark and Curran, 2007) , sentence r... | 0 |
Machine reading comprehension (MRC) is essentially formed as a question-answering (QA) task subject to a given context like passages (Hermann et al., 2015; Rajpurkar et al., 2016) . Recently, more and more attention is raised on a special MRC type whose given context is a dialogue text (Reddy et al., 2019; Choi et al.,... | 0 |
Data-to-text generation aims to create natural language text to describe the input data (Reiter and Dale, 2000) . Here we focus on structured text input in a particular form such as a tree or a graph. Figure 1 shows an example where the input data is a mini knowledge graph, and the output text is its corresponding natu... | 0 |
Sub-sentential paraphrases can be acquired from text pairs expressing the same meaning . If the semantic similarity of a text pair has a direct impact on the quality of the acquired paraphrases, it has, to our knowledge, never been shown what impact the type of original signal has on paraphrase acquisition. In this wor... | 0 |
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