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There is a rich literature in natural language processing (NLP) and information retrieval on question answering (QA) (Hirschman and Gaizauskas, 2001) , but recently deep learning has sparked interest in a special kind of QA, commonly referred to as reading comprehension (RC) (Vanderwende, 2007) . The aim in RC research... | 0 |
Twitter is one of the most popular micro-blogging platforms in recent days. There are over 500 million tweets posted per day 1 including real-world events described on Twitter which range from short and daily life events (e.g. falling to the ground) to long and widely-broadcasted events (e.g. a match in World Cup). Suc... | 0 |
Iterative bootstrapping algorithms have been proposed to extract semantic lexicons for NLP tasks with limited linguistic resources. Bootstrapping was initially proposed by Riloff and Jones (1999) , and has since been successfully applied to extracting general semantic lexicons (Riloff and Jones, 1999; Thelen and Riloff... | 0 |
Tree Adjoining Grammars are a extension of CFG introduced by Joshi in that use trees instead of productions as the primary representing structure. Several parsing algorithms have been proposed for this formalism, most of them based on tabular techniques, ranging from simple bottom-up algorithms (Vijay-Shanker and Joshi... | 0 |
Word relatedness between two words refers to the degree of how much one word has to do with another word whereas word similarity is a special case or a subset of word relatedness. A word relatedness method has many applications in NLP, and related areas such as information retrieval (Xu and Croft, 2000) , image retriev... | 0 |
The similarity between connectionist models of computation and neuron computation suggests that a study of syntactic parsing in a connectionist computational architecture could lead to significant insights into ways natural language can be parsed efficiently. Unfortunately, previous investigations into connectionist pa... | 0 |
The development of software packages and code libraries that implement algorithms and perform tasks in scientific areas is of great advantage for both researchers and educators. The availability of these tools saves the researchers a lot of the time and the effort needed to implement the new approaches they propose and... | 0 |
It was probably Chuck who coined the term "armchair linguist" (Svartvik, 1991) . Chuck Fillmore's deep commitment to the study of language -in particular lexical semantics -on the basis of corpus data served as a model that kept many of us honest in our investigation of language. Today, we are lucky to be able to work ... | 0 |
The increasing availability of large-scale corpus resources has had a lasting impact on the field of linguistics. In the field of corpus linguistics, large quantities of data have made it possible to precisely model complex multifactorial processes of linguistic change (e.g. Perek and Hilpert, 2017; Gries et al., 2018)... | 0 |
Lexical sample task is a kind of WSD evaluation task providing training and test data in which a small pre-selected set of target words is chosen and the target words are marked up. In the training data the target words' senses are given, but in the test data are not and need to be predicted by task participants.HIT-IR... | 0 |
In recent years, simultaneous translation has attracted increasing interest both in research and industry community. It aims at a real-time translation that demands high translation quality and an as-short-as-possible delay between speech and translation output.A typical simultaneous translation system consists of an a... | 0 |
The evolution of social media texts such as blogs, micro-blogs (e.g., Twitter), and chats (e.g., WhatsApp and Facebook messages) has created many new opportunities for information access and language technologies. However, it has also posed many new challenges making it one of the current prime research areas in Natura... | 0 |
In this paper, we introduce the Action ENRICH4ALL (E-goverNment [RI] CHatbot for ALL) which is about the development of a multilingual chatbot service to be deployed in public administration in Luxembourg, Denmark, and Romania. ENRICH4ALL is funded by the Connecting Europe Facility and its duration is from June 2021 to... | 0 |
Sequence to sequence model decoding remains something of a paradox. The most widely adopted training method for these models is maximum likelihood estimation (MLE), which aims at maximising the probability of the ground truth outputs provided in the training datasets. Consequently, decoding from MLE-trained models is d... | 0 |
Reference problems are a central issue in natural language processing. For instance, we need to understand the antecedents of pronouns in translating one language into another. Consider: Someone killed Jim. The police have no suspect, but they think that he or she needed money and knew that he was a wealthy man. He wal... | 0 |
Being able to converse like humans in a closed domain is a precondition before an intelligent opendomain chatbot, which further requires transiting among various domains, can be designed Su et al., 2020) . Nonetheless, even if constrained in a specific domain, current chatbots are still far from satisfactory. Unlike ta... | 0 |
Since the introduction of Semantic Textual Similarity (STS) task at SemEval 2012 and the Semantic Relatedness (SR) task at SemEval 2014, a large number of participating systems have been developed to resolve the tasks. 1, 2 The systems must quantifiably identify the degree of similarity, relatedness, respectively, for ... | 0 |
Coreference resolution refers to the task of identifying noun phrases that refer to the same extralinguistic entity in a text. Using coreference information has been shown to be beneficial in a number of other tasks, including information extraction (McCarthy and Lehnert, 1995) , question answering (Morton, 2000) and s... | 0 |
Machine reading comprehension (MRC) or question answering (QA) has been a long-standing goal in Natural Language Processing. There is a surge of interest in this area due to new end-to-end modeling techniques and the release of several largescale, open-domain datasets.In earlier datasets (Hermann et al., 2015; Hill et ... | 0 |
Question Answering (QA) is a challenging task that draws upon many aspects of NLP. Unlike search or information retrieval, answers infrequently contain lexical overlap with the question (e.g. What should we eat for breakfast? -Zoe's Diner has good pancakes), and require QA models to draw upon more complex methods to br... | 0 |
Natural language processing (NLP) is enamored of contextual word representations-and for good reason! Contextual word-embedders, e.g. BERT (Devlin et al., 2019) and ELMo (Peters et al., 2018) , have bolstered NLP model performance on myriad tasks, such as syntactic parsing (Kitaev et al., 2019) , coreference resolution... | 0 |
Technical terms and named entities (NEs) constitute the bulk of the Out Of Vocabulary (OOV) words. Named entities are usually not found in bilingual dictionaries and are very generative in nature. Proper identification, classification and translation of Named entities (NEs) are very important in many Natural Language P... | 0 |
Language identification (LID) is an important NLP task that usually acts as an enabling technology in a pipeline involving another downstream task such as machine translation (Salloum et al., 2014) or sentiment analysis (Abdul-Mageed, 2017b,a). Although several works have focused on detecting languages in global settin... | 0 |
Over recent years there has been much interest in the field of distributional semantics, drawing on the distributional hypothesis: words that occur in similar contexts tend to have similar meanings (Harris, 1954) . There is a large body of work on the use of different similarity measures (Lee, 1999; Weeds and Weir, 200... | 0 |
Various tasks dealing with natural language data have to cope with the numerous different senses possessed by every lexical item: machine translation, information retrieval, information extraction ... This very old issue is far from being solved, and evaluation of methods addressing it is far from obvious (Resnik and Y... | 0 |
Currently an important portion of research in natural language processing is devoted to the goal of reducing or getting rid of large labeled datasets. Recent examples include language model fine-tuning (Devlin et al., 2019) , transfer learning (Zoph et al., 2016) or few-shot learning (Brown et al., 2020) . Another comm... | 0 |
De nombreux auteurs ont souligné combien les énoncés que nous produisons quotidiennement contiennent un grand nombre d'expressions figuratives qui posent des problèmes tant aux modèles psychologiques de la compréhension du langage qu'aux approches linguistiques en traitement automatique de la langue (Gibbs, 1994; Marti... | 0 |
Question Answer (QA) ranking, or the task of accurately ranking the best answers to an input question, has been a long-standing research pursuit with practical applications in a variety of domains. Popular examples of such applications are customer support chat-bots, community question answering portals, and digital as... | 0 |
Word embeddings are an essential component in systems for many natural language processing tasks such as part-of-speech tagging (Al-Rfou' et al., 2013) , dependency parsing (Chen and Manning, 2014) and named entity recognition (Pennington et al., 2014) . Cross-lingual word representations provide a shared space for wor... | 0 |
Neural machine translation (Kalchbrenner and Blunsom, 2013; Sutskever et al., 2014; which directly leverages a single neural network to transform the source sentence into the target sentence, has drawn more and more attention in both academia and industry (Shen et al., 2015; Johnson et al., 2016; Gehring et al., 2017; ... | 0 |
Il est aujourd'hui un consensus clair, non seulement que les corpus annotés sont indispensables aux outils de traitement automatique des langues (TAL) pour leur entraînement et leur évaluation, mais également que l'annotation doit être consistante pour être profitable (voir, par exemple (Reidsma et Carletta, 2008) ). O... | 0 |
Tim increased inl;erest in collocation ext;raetion comes from t;hu faeI; l;hal, t;hey can be used for many NLP at)plical;ions such as machine transla-(;ion, maehilw, aids R)r t;ra.nslal,ion, dictionary consl;ru(:i;ion, and secon(1 language learning, t.o mmm a few.Recently, large scale textual corpora give the potential... | 0 |
Response selection remains at the core of conversation modeling, with the objective of selecting an appropriate response utterance from a set of candidate utterances, for a given conversation history consisting of previous utterances (context). Decades of research in this task includes traditional methods such as (Kita... | 0 |
Traditional recommendation systems factorize users' historical data (i.e., ratings on movies) to extract common preference patterns (Koren et al., 1 https://github.com/facebookresearch/ParlAI 2009; He et al., 2017b) . However, besides making it difficult to accommodate new users because of the cold-start problem, relyi... | 0 |
With the rapid development of deep neural networks and parallel computing, distributed representation of knowledge attracts much research interest. Models for learning distributed representations of knowledge have been proposed at different granularity level, including word sense level (Huang et al., 2012; Neelakantan ... | 0 |
Inducing factual information during response generation has garnered a lot of attention in dialogue systems research. While language models Zheng et al., 2020) have been shown to generate responses akin to the dialogue history, they seldom contain factual information, leading to a bland conversation with the agent. Kno... | 0 |
Lately, deep learning conversational systems have seen increasing interest from industry and academia alike (Chen et al., 2017) . These systems find usage in various contexts, starting from personal speech assistants like Google Assistant through the "chatbots" on instant messaging platforms like Facebook Messenger, an... | 0 |
Hand-built NLP grammars frequently have a depth of linguistic representation and constraints not present in current treebanks, giving them potential importance for tasks requiring deeper processing. On the other hand, these manually built grammars need to solve the disambiguation problem to be practically usable.This p... | 0 |
In recent years, soft-attention based neural machine translation models (Bahdanau et al., 2015; Gehring et al., 2017; Hassan et al., 2018) have achieved state-of-the-art results on different machine translation tasks. The soft-attention mechanism computes the context (encoder-decoder attention) vector for each target t... | 0 |
Owing to notable advances in deep learning and representation learning, important progress has been achieved on text classification, reading comprehension, and other NLP tasks. Recently, pretrained language representations with self-supervised objectives (Peters et al., 2018; Devlin et al., 2018; Radford et al., 2018) ... | 0 |
In this paper, we study the effect of non-normalized text on natural language processing (NLP). Non-normalized text includes non-canonical word forms, noisy word forms, and word forms with "small" perturbations, such as informal spellings, typos, scrambled words. Compared to normalized text, the variability of non-norm... | 0 |
Summarization of meetings faces many challenges not found in texts, i.e., high word error rates, absence of punctuation, and sometimes lack of grammaticality and coherent ordering. On the other hand, meetings present a rich source of structural and pragmatic information that makes summarization of multi-party speech qu... | 0 |
In the Fourth SIGHAN Bakeoff, besides providing the evaluation tasks for the word segmentation and NER, it also introduced another important evalua-tion task, POS tagging for Chinese language. In this bakeoff, our models built for the tasks are similar to that in the work of Ng and Low (2004) . The models are based on ... | 0 |
Recent work in unsupervised and self-supervised pre-training has revolutionised the field of natural language understanding (NLU), resulting in high performance ceilings across multiple tasks (Devlin et al., 2019; Dong et al., 2019) . The recent success of language model pre-training with masked language modelling (MLM... | 0 |
In recent years, contextual embeddings (Peters et al., 2018; Devlin et al., 2018) have made immense progress in semantic understanding-based tasks. After being trained using large amounts of data, for example via a self-supervised task like masked language-modeling, such models learn crucial elements of language, such ... | 0 |
One of the major challenges of entity linking is resolving contextually polysemous mentions. For example, Germany may refer to a nation, to that nation's government, or even to a soccer team. Past approaches to such cases have often focused on collective entity linking: nearby mentions in a document might be expected t... | 0 |
The blogosphere, which is a subset of the web and is comprised of personal electronic journals (weblogs) currently encompasses 27.2 million pages and doubles in size every 5.5 months (Technorati, 2006) . The information contained in the blogosphere has been proven valuable for applications such as marketing intelligenc... | 0 |
Word embeddings capture distributional similarities and thus inherit demographic stereotypes (Bolukbasi et al., 2016) . Such embedding biases tend to track statistical regularities such as the percentage of people with a given occupation (Nikhil Garg and Zou, 2018) but sometimes deviate from them (Bhatia, 2017) . Recen... | 0 |
Social media texts attract a lot of attention in the fields of information extraction and text mining. Although texts of this type contain a lot of information, such as one's reputation or emotions, they often contain non-standard tokens (lexical variants) that are considered out-of-Vocabulary (OOV) terms. We define an... | 0 |
Many words have multiple meanings, and the process of identifying the correct meaning, or sense of a word in context, is known as word sense disambiguation (WSD). Among the various approaches to WSD, corpus-based supervised machine learning methods have been the most successful to date. With this approach, one would ne... | 0 |
Microblogging websites have been a huge source of data containing different kinds of information. Since the users on these microblogging websites tend to write informal real-time messages, they also tend to mix languages as they are just being spontaneous and want to ease the communication or they are just multilingual... | 0 |
In this paper, we present our preliminary work on automatic scoring of a summarization task that is designed to measure the reading comprehension skills of students from grades 6 through 9. We first introduce our underlying reading comprehension assessment framework (Sabatini and O'Reilly, In Press; Sabatini et al., In... | 0 |
In multi-modal translation, the task is to translate from a source sentence and the image that it describes, into a target sentence in another language. As both automatic image captioning systems and crowd captioning efforts tend to mainly yield descriptions in English, multi-modal translation can be useful for generat... | 0 |
Vector space models of semantics frequently employ some form of dimensionality reduction for improvement in representations or computational overhead. Many of the dimensionality reduction algorithms assume that the unreduced word space is linear. However, word similarities have been shown to exhibit many non-metric pro... | 0 |
In the area of media analysis, one of the key tasks is collecting detailed information about opinions and attitudes toward specific topics from various sources, both offline (traditional newspapers, archives) and online (news sites, blogs, forums). Specifically, media analysis concerns the following system task: given ... | 0 |
Recent studies have exposed the vulnerability of ML models to adversarial attacks, small input perturbations which lead to misclassification by the model. Adversarial example generation in NLP (Zhang et al., 2019) is more challenging than in commonly studied computer vision tasks (Szegedy et al., 2014; Kurakin et al., ... | 0 |
Online social media platforms are dealing with an unprecedented scale of offensive (e.g., hateful, threatening, profane, racist, and xenophobic) language (Twitter; Facebook; Reddit) . Given the scale of the problem, online social media platforms now increasingly rely on machine learning based systems to proactively and... | 0 |
The Task # 2 of Semeval 2012 focuses on measuring the degree of relational similarity between the reference words pairs (training) and the test pairs for a given class (Jurgens et al., 2012) .The training data set consists of 10 classes and the testing data set consists of the 69 classes. These datasets as well as the ... | 0 |
Identification of cognates and recurrent sound correspondences is a component of two principal tasks of historical linguistics: demonstrating the relatedness of languages, and reconstructing the histories of language families. Manually compiling the list of cognates is an error-prone and time-consuming task. Several me... | 0 |
The aim of the shared task is to research and develop automatic systems that can help mental health professionals with the process of triaging posts with ideations of depression and/or self-harm. We structured our participation in the CLPsych 2016 shared task in order to focus on different facets of modelling online fo... | 0 |
Transformer-based neural language models, such as BERT (Devlin et al., 2018) , have achieved state-of-the-art performance for a variety of natural language processing (NLP) tasks. Since most are pre-trained on large general domain corpora, many efforts have been made to continue pretaining general-domain language model... | 0 |
In recent years, optical character recognition of printed text has reached high accuracy rates for modern fonts. However, historical documents still pose a challenge for character recognition and OCR of those documents still does not yield satisfying results. This is a problem for all researchers who would like to use ... | 0 |
Paraphrase identification is an area of research with a long history. Approaches to the task can be divided into supervised methods, such as (Madnani et al., 2012) , currently the most commonly used, and unsupervised techniques (Socher et al., 2011) .While many approaches of both types use carefully selected features t... | 0 |
A great deal of linguistic knowledge is encoded implicitly in bilingual resources such as parallel texts and bilingual dictionaries. Dyvik (1998 Dyvik ( , 2005 has provided a knowledge discovery method based on the semantic relationship between words in a source language and words in a target language, as manifested in... | 0 |
One of the important reasons for communication is the desire on the part of the members to express their emotions (Millar 1951) . Language is the effective tool to carry out this task and speech is the most efficient mode of language communication between humans. In the recent years, emotion recognition in human speech... | 0 |
Multi-document summarization (MDS) is the summarization of a collection of related documents (Mani (1999) ). Its application includes the summarization of a news story from different sources where document sources are related by the theme or topic of the story. Another application is the tracking of news stories from t... | 0 |
In recent years, an intense research focus on machine translation (MT) has raised the quality of MT systems to the degree that they are now viable for a variety of real-world applications. Because of this, the research community has turned its attention to a major drawback of such systems: they are still quite slow. Re... | 0 |
Over the past couple of years, we witness tremendous advances of language models in solving various Natural Language Processing (NLP) tasks. Most of the time, these models were trained on large datasets, each model pushing the limits of the other. With this success came a dire need to interpret and analyze the behavior... | 0 |
We participated in the WMT shared news translation task and focus on the bidirections: English and Khmer, English and Pashto. We applied fairseq as our develop tool and use transformer (Vaswani et al., 2017) as the main architecture. The primary ranking index for submitted systems is BLEU (Papineni et al., 2002) , ther... | 0 |
In 2013, World Economic Forum (WEF) listed massive digital misinformation as one of the top global risks likely to occur in 10 years 1 . Unfortunately, we witnessed many unpleasant incidents due to misinformation spread over Internet such as massive stock price changes 2 , gunfights 3 , and others. Since the start of C... | 0 |
As the volume of information present on the internet steeply increases, automatic fact-checking has become a promising approach to identify and stop the spread of misinformation. Active research in this area has been supported in part by a handful of carefully curated datasets (Thorne et al., 2018a; Hanselowski et al.,... | 0 |
Named Entity Recognition (NER) is an important tool in almost all NLP application areas such as information retrieval, machine translation, ques tion-answering system, automatic summarization etc. Proper identification and classification of NEs are very crucial and pose a very big challenge to the NLP researchers. The ... | 0 |
Research on human perception has shown that world knowledge supports the processing of sensory information (Mitterer et al., 2009; Ishizu, 2013) . For instance, humans have been found to use their knowledge about typical colours of an object when perceiving an instance of that object, in order to compensate for, e.g., ... | 0 |
As a result of the world getting more connected and digitized, cyber attacks become increasingly common and pose serious issues for the society. More recently in 2017, a ransomware called Wan-naCry, which has the capability to lock down the data files using strong encryption, spread around the world targeting public ut... | 0 |
Previous work has brought up multiple legal assistant systems with various functions, such as finding relevant cases given the query , providing applicable law articles for a given case (Liu and Liao, 2005) and etc., which have substantially improved the working efficiency. As legal assistant systems, charge prediction... | 0 |
Nobody reads all available user-generated comments about products they might buy. Summarizing reviews in a short paragraph would save valuable time, as well as provide better insights into the main opinions of previous buyers. In addition to traditional difficulties of summarization, the specific setting of opinion sum... | 0 |
Language models (LMs) are one of the most fundamental technologies in NLP, with applications spanning text generation (Bahdanau et al., 2015; Rush et al., 2015) , representation learning (Peters et al., 2018; Devlin et al., 2019; Yang et al., 2019) , and few-shot learning (Radford et al., 2019; Brown et al., 2020) . Mo... | 0 |
Lexical ambiguity, an inherent phenomenon in natural languages, refers to words or phrases that can have multiple meanings. In written text, lexical ambiguity can be roughly characterized into two categories: polysemy and homonymy. A polysemous word has multiple senses that express different but related meanings (e.g. ... | 0 |
La géolinguistique étudie la variation des phénomènes linguistiques dans l'espace, qu'elle peut discrétiser avec un degré de granularité plus ou moins fin. Depuis le début du XX e siècle, époque à laquelle les atlas dialectologiques ont connu un certain intérêt, le paysage linguistique de la France et de l'Europe a con... | 0 |
Biomedical named entity recognition (NER) is a computational technique used to identify and classify strings of text (mentions) that designate important concepts in biomedicine. Over the last fourteen years there has been considerable interest in this problem with a variety of generic and entity-specific algorithms app... | 0 |
Social media platforms such as Twitter are regarded as potentially valuable tools for monitoring public health, including identifying ADEs to aid pharmacovigilance efforts. They do however pose a challenge due to the relative scarcity of relevant tweets in addition to a more fluid use of language, creating a further ch... | 0 |
In human-human tutoring, it is an effective strategy to ask students to explain instructional material in their own words. Self-explanation (Chi et al., 1994) and contentful talk focused on the domain are correlated with better learning outcomes (Litman et al., 2009; Chi et al., 1994) . There has therefore been much in... | 0 |
Contrastive learning learns to encode data into an embedding space such that related data points have closer representations and unrelated ones have further apart ones. Recent works in NLP adopt deep neural nets as encoders and use unsupervised contrastive learning on sentence representation (Giorgi et al., 2020 ), tex... | 0 |
SemEval-2017 Task 3 1 on Community Question Answering (cQA) focuses on answering new questions by retrieving related answered questions in community forums (Nakov et al., 2017) . This task extends the previous SemEval-2015 and SemEval-2016 cQA tasks.This year, five subtasks were proposed: English Question-Comment Simil... | 0 |
Deep neural networks have achieved state-of-theart performances for many natural language processing (NLP) tasks (Otter et al., 2020; Ruder et al., 2019) . When applying such models in real world applications, understanding their behavior can be challenging -the ever increasing complexity of such models makes it diffic... | 0 |
Vision-language tasks, such as image captioning (Vinyals et al., 2015) , visual question answering (Antol et al., 2015) , and visual commonsense reasoning (Zellers et al., 2018) , serve as rich test-beds for evaluating the reasoning capabilities of visually informed systems. These tasks require joint understanding of v... | 0 |
Named entity recognition (NER) is the basic step of many natural language processing (NLP) tasks, such as Information Extraction and MachineTranslation. NER's recognition precision will directly affect subsequent NLP tasks.Mongolian has a wide range of users in China, Mongolia and Russia. However, it is a low-resource ... | 0 |
Arabic is a morphologically complex language. 1 The morphological analysis of a word consists of determining the values of a large number of (orthogonal) features, such as basic part-of-speech (i.e., noun, verb, and so on), voice, gender, number, information about the clitics, and so on. 2 For Arabic, this gives us abo... | 0 |
In radiology, the health status of a patient is described using a multitude of formats. During the examination process, a radiologist creates machine readable descriptions such as radiology images, dictated reports about the image findings and written texts. Although, most of the radiology data are related via the anat... | 0 |
Cross-Document (CD) Event Coreference resolution is the task of identifying clusters of text mentions, across multiple texts, that refer to the same event. Successful identification of such coreferring mentions is beneficial for a broad range of applications at the multi-text level, which are gaining increasing interes... | 0 |
Though WordNet was already used as a starting resource for developing many language WordNets, the constructions of the WordNet for languages can be varied according to the availability of the language resources. Some were developed from scratch, and some were developed from the combination of various existing lexical r... | 0 |
Assigning sense tags to the words in a text can be viewed as a classification problem. A probabilistic classifier assigns to each word the tag that has the highest estimated probability of having occurred in the given context. Designing a probabilistic classifier for word-sense disambiguation includes two main sub-task... | 0 |
The use of machine translation (MT) as part of the localization workflow has mushroomed in recent years, with post-edited MT becoming an increasingly cost-effective solution for specific domains and language pairs. DePalma and Hegde (2010) stated that 42% of language service providers (LSPs) surveyed said that they off... | 0 |
The Mycenaean script constitutes one of the writing systems used in the Aegean in the 2nd millennium B.C. Mycenaean Linear B, was a syllabic script deciphered by the English architect Michael Ventris in 1-6-1952, who proved that it expresses an archaic form of the Greek language. The Mycenaean Linear B texts, though th... | 0 |
Word Segmentation (WS) is an essential process for several Natural Language Processing (NLP) tasks such as Part-of-Speech (PoS) tagging and Machine Translation (MT). The accuracy of WS significantly affects the accuracy of these NLP tasks, as shown in experimental results from Nguyen et al. and Chang et al. While WS is... | 0 |
Mental health care has been of great importance as the ongoing COVID-19 pandemic poses a serious negative impact on people's mental wellbeing (Paredes et al., 2021) . Not only there is a larger unmet need for counseling services, the health care workers are also in tremendous physical and mental strain (Huffman et al.,... | 0 |
The editing of semi-automatic translations has been a common practice among users of Translation Memory (TM). TM tools such as SDL Trados 1 and Wordfast 2 provide user-friendly environments to aid human translators. The post-editing (PE) of Machine Translation (MT) output has only recently started to be more widely ado... | 0 |
Modern weather reports present weather prediction information using tables, graphs, maps, icons and text. Among these different modalities only text is currently manually produced, consuming significant human resources. Therefore releasing meteorologists' time to add value elsewhere in the production chain without sacr... | 0 |
Entity linking (EL) describes the task of disambiguating entity mentions in a text by linking them to a knowledge base (KB), e.g. the text span Earl of Orrery can be linked to the KB entry John Boyle, 5 th Earl of Cork, thereby disambiguating it. EL is highly relevant in many fields like digital humanities, classics, t... | 0 |
Past successes with conversational Intelligent Tutoring Systems (ITS) (Graesser et al., 2001) , have helped to demonstrate the efficacy of computer-led, tutorial dialogue. However, ITS will not reach their full potential until they can overcome current limitations in spoken dialogue technologies. Producing systems capa... | 0 |
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