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Unlike sentence-level neural machine translation (NMT), document-level NMT needs to not only model intra-sentence dependencies, but also consider a wide variety of inter-sentence discourse phenomena, such as coreference, lexical cohesion, semantic coherence, discourse relations. Motivated by the success of "one transla... | 0 |
Many NLP systems are based on lexical data. The development costs of such data are a major drawback in such NLP systems. Furthermore, the existing lexical data have generally been developed for a specific purpose and can't be reused easily in other applications. The Papillon project applies some tools and methods to de... | 0 |
Recent advances in deep neural networks have created applications for a range of different domains. In spite of the promising performance achieved by neural models, there are concerns around their robustness, as evidence shows that even a slight perturbation to the input data can fool these models into producing wrong ... | 0 |
An interesting task in temporal information processing is how to identify a temporal relation between a pair of temporal entities such as events (EVENT) and time expressions (TIMEX) in a narrative. After the publication of TimeBank (Pustejovsky et al., 2003b) annotated in TimeML (Pustejovsky et al., 2003a) , supervised... | 0 |
The standard methods for inferring the parameters of probabilistic models in computational linguistics are based on the principle of maximum-likelihood estimation; for example, the parameters of Probabilistic Context-Free Grammars (PCFGs) are typically estimated from strings of terminals using the Inside-Outside (IO) a... | 0 |
The task of Abstract Meaning Representation (AMR) parsing translates a natural sentence into a rooted directed acyclic graph capturing the semantics of the sentence, with nodes representing concepts and edges representing their relations (Banarescu et al., 2013) . Recent works utilizing pretrained encoder-decoder langu... | 0 |
Two trends drive significant interest in automating the process of medical documentation: a growing shortage of clinicians in the United States and a rise in clinician burnout rates due to health information technology-related stress (Gidwani et al., 2017; AAMC, 2019; Gardner et al., 2019) . Clinicians today are respon... | 0 |
Probabilistic topic models such as Latent Dirichlet allocation (LDA) (Blei et al., 2003) , are widely used to uncover hidden topics within a text corpus. LDA models each document as a mixture of topics where each topic is a distribution over words. In essence, LDA reveals latent topics in a corpus by implicitly capturi... | 0 |
The majority of recent work in semantic role labeling (SRL) has been carried out on PropBankstyle semantic argument annotations (Palmer et al., 2005) , rather than on FrameNet-style annotations (Ruppenhofer et al., 2006) . FrameNet differs from PropBank in that FrameNet annotations are more strongly semantically driven... | 0 |
The Distributional Hypothesis, summarised by the memorable line of Firth (1957) -You shall know a word by the company it keeps -has inspired a diverse range of research in natural language processing. In such work, a word is represented by the distribution of other words that co-occur with it. Distributional representa... | 0 |
The Chinese comma, which looks graphically very similar to its English counterpart, is functionally quite different. It has attracted a significant amount of research that studied the problem from the viewpoint of natural language processing. For example, Jin et al ( 2004) and Li et al ( 2005) view the disambiguation o... | 0 |
We start with a peculiar observation: even though polysemy and homonymy are common phenomena of natural language, i.e. many words have more than one meaning, this does not create a considerable obstacle in our day-to-day comprehension of texts and conversations. For example, the word charge has 40 different senses in E... | 0 |
Semantic similarity measures and relations are proven to be valuable for various NLP and IR applications, such as word sense disambiguation, query expansion, and question answering.Let R be a set of synonyms, hypernyms, and co-hyponyms of terms C, established by a lexicographer. A semantic relation extraction method ai... | 0 |
Recently, several feed-forward neural networkbased language and translation models have achieved impressive accuracy improvements on statistical machine translation tasks (Allauzen et al., 2011; Le et al., 2012b; Schwenk et al., 2012) . In this paper we focus on recurrent neural network architectures, which have recent... | 0 |
La désambiguïsation sémantique d'un texte consiste à déterminer le sens correct des mots de ce texte. Des campagnes d'évaluation comme SENSEVAL sont la preuve du grand intérêt porté au sein de notre communauté à cette tâche (90 équipes ont mentionné leur intérêt à participer à la prochaine campagne SENSEVAL3).Cet intér... | 0 |
Incorporating linguistic information into statistical Natural Language Processing (NLP) applications usually helps to improve a particular NLP. Simplifying the problem beforehand, for languages with complex language constructions, is one of the approaches that is usually applied, especially when the constructions canno... | 0 |
In this paper, we present a robust parsing approach called supertagging that integrates the flexibility of linguistically motivated lexical descriptions with the robustness of statistical techniques. The idea underlying the approach is that the computation of linguistic structure can be localized if lexical items are a... | 0 |
MORPA is a MORphological PArser developed for use in the text-to-speech conversion system for Dutch, SPRAAKMAKER [van Leeuwen and te Lindeft, 1993 ]. An important step in text-to-speech conversion is the generation of the correct phonemic representation on the basis of the input text. As is wellknown, phonemic transcri... | 0 |
There has been a growing interest in text mining applications that can automatically detect opinions, facts and sentiments in texts. Many of the current opinion or sentiment mining applications use a crude division between negative, neutral and positive sentiments. Modality, defined from a linguistic perspective as the... | 0 |
Influenza is a highly contagious acute respiratory disease caused by influenza virus. As the highly genetic variation, influenza can cause global epidemic, which not only brought huge dis-asters to people's life and health, but also have significant disruptions to economy. There are about 10-15% of people who get influ... | 0 |
Emotion not only is a key driver to people's actions and thoughts, but also is a fundamental part of human communication. As such, emotion recognition technology has become growingly important in improving how humans interact with machines [1] . For instance, emotion recognition has been applied to analyze people's rea... | 0 |
It is currently estimated that over 1.5 billion people are learning English as a Second Language (ESL) worldwide. Their learning progress is commonly evaluated with classroom tests prepared by language instructors, quizzes in language learning software such as Duolingo and Rosetta Stone, and by official standardized la... | 0 |
Counterfactual reasoning -mentally simulating what would have happened if conditions were different -is a common tool for making causality assessments (Kahneman and Tversky, 1981) , which in turn are crucial for model evaluation, error analysis, and explanation (Miller, 2019) . For example, in Figure 1 , "It is great f... | 0 |
Machine translation is now a serious alternative to manual translation. Many organisations and businesses employ MT-systems and for various purposes. Some use MTsystems for information purposes (gisting of material in "exotic" languages), some as a basis for decision-making (as to which documents to provide high-qualit... | 0 |
Word alignment is the problem of identifying translationally equivalent words across the languages of a parallel text. It has found widespread use for enabling applications such as statistical machine translation (Brown et al., 1993; Koehn et al., 2003) , annotation transfer , word sense disambiguation (Diab and Resnik... | 0 |
The goal of this paper is to demonstrate an issue that complicates the comparison and replication of named entity recognition (NER) systems. Standard F1-based evaluation of NER models in the manner made popular by the CoNLL 2002-3 shared tasks (Tjong Kim Sang, 2002; Tjong Kim Sang and De Meulder, 2003) requires decodin... | 0 |
This paper 1 is concerned with the problem of controlling the output of natural language generation (NLG) systems. In many application scenarios the generator's task is underspecified, resulting in multiple possible solutions (texts expressing the desired content), all equally good to the generator, but not equally app... | 0 |
Thetis focuses on the creation and localization of enhanced on-line pedagogical content for language learning in tourism industry. It is based on a general approach to language learning that allows employees to acquire practical oral and written skills 1 THETIS -Training for hotel employees to interact in situations (E... | 0 |
The purpose of a statistical language model is to assign high probabilities to likely word sequences and low probabilities to unlikely ones. The challenge here arises from the combinatorially large number of possibilities, only a fraction of which can ever be observed. In general, language models must learn to recogniz... | 0 |
Question-answering systems aim at giving short and precise answers to natural language questions. These systems are quite complex, and include many different components. Question-Answering systems are generally organized within a pipeline which includes at a high level at least three components: questions processing, s... | 0 |
Extracting knowledge from scientific articles is a challenging but very important problem. This becomes especially critical for biomedical literature which is growing at an increasing rate of at least 4% per year, as of June 2019 there are 30 Million documents in PubMed (Lu, 2011) . Named Entity Recognition (NER) (Sett... | 0 |
Computational lexicons providing accurate lexical-syntactic information, such as subcategorization frames (SCFs) are vital for many NLP applications involving parsing and word sense disambiguation. In parsing, SCFs have been successfully used to improve the output of statistical parsers (Klenner (2007) , Deoskar (2008)... | 0 |
Probing studies into large contextual word embeddings such as BERT (Devlin et al., 2019) have shown that these deep multi-layer models essentially reconstruct the traditional NLP pipeline capturing syntax and semantics (Jawahar et al., 2019) ; information such as part-of-speech tags, constituents, dependencies, semanti... | 0 |
This work presents several experiments performed on dependency parsing of the Basque Dependency Treebank (BDT) [1] . Several syntactic analyzers based on dependencies have been developed, with proposals ranging from systems that directly construct dependency structures [9] to other systems based on the more traditional... | 0 |
Hiero (Chiang, 2007) models translation using a lexicalized synchronous context-free grammar (SCFG) extracted from word aligned bitexts. Typically, CKY-style decoding is used for Hiero with time complexity O(n 3 ) for source input with n words. Scoring the target language output using a language model within CKY-style ... | 0 |
Log-linear models have been used in many areas of Natural Language Processing (NLP) and Information Retrieval (IR). Scenarios in which log-linear models have been applied often involve simple binary classification decisions or probability assignments, as in the following three examples: Ratnaparkhi et al. (1994) consid... | 0 |
Making an anagram is one of the most popular wordplay games and has a long history that can be traced back to the time of the Ancient Greeks (Wheatley, 1862) . An anagram is a sentence or a phrase that is made as a permutation of characters of an input sentence or phrase. For example, "Trims cash" is an anagram of "Chr... | 0 |
Word sense disambiguation (WSD) is the problem of assigning a sense to an ambiguous word, using its context. We assume that different senses of a word correspond to different entries in its dictionary definition. For example, suit has two senses listed in a dictionary: 'an action in court,' and 'suit of clothes.' Given... | 0 |
The use of machine learning for natural language processing tasks has been steadily increasing over the years: text processing challenges such as those associated with the SemEval workshops (Erk and Strapparava, 2010) and the I2B2 medical informatics shared tasks (i2b2 team, 2011) are well known, and tools for training... | 0 |
In natural language text, it is very common for a word to have more than one sense. For example, in a sentence "An airline hires new cabin crews" of Figure 1 , the words 'airline,' 'hires,' 'new,' 'cabin' and 'crews' have more than two senses. In this case, we can map 'airline' to 'airline Noun#2', 'hires' to 'hire Ver... | 0 |
Textual emotion analysis is becoming increasingly important due to augmented communication via computer mediated communication (CMC) . A possible application of textual emotion recognition is online chat system. An emotion feedback system can recognize users' emotion and give appropriate responses. Another application ... | 0 |
The increasing volume of text posted by users on the web is regarded as an extremely useful opportunity to reveal public opinion on many issues. For a variety of reasons, governments, companies, political candidates, and consumers want to explore such web content. This type of text is referred to in the literature as U... | 0 |
In this paper we describe the current state of a new lexical resource: the Hinoki treebank. The motivation and initial construction was described in detail in Bond et al. (2004a) . The ultimate goal of our research is natural language understanding -we aim to create a system that can parse text into some useful semanti... | 0 |
Contextualized word-embedding models, such as BERT (Devlin et al., 2019) and XLNet (Yang et al., 2019) , rely on sub-word units called wordpieces (Johnson et al., 2017) , that enable these models to generalize over frequent charactersequences and elegantly handle out-of-vocabulary items (with minimal resort to characte... | 0 |
In recent years, the interest in obtaining structured data from unstructured resources has been increased, namely due to the exponential growth of information in the Web. Regarding this objective, Relation Extraction (RE) aims to automatically identify semantic relations between entities. For instance, from the sentenc... | 0 |
Statistical machine translation (SMT) is a datadriven approach. The quantity and quality of parallel data is crucial to build high performance SMT systems. Nonetheless, nowadays parallel corpora are still limited in quantity, genre and language coverage. In particular, the languages with less native speakers are less i... | 0 |
Korean is a non-con gurational, postpositional, agglutinative language. Postpositions, such as noun-endings, verb-endings, and pre nal verbendings, are morphemes that determine the functional role of NPs noun phrases and VPs verb phrases in sentences and also transform VPs into NPs or APs adjective phrases. Since a seq... | 0 |
Online learning platforms aim to provide personalised tutoring at scale using data-driven personalisation (Romero and Ventura, 2010) . A key component of a personalised system is a recommendation algorithm that suggests the next learning activity. To ensure that the recommendation is tailored to the student's level and... | 0 |
La langue amazighe du Maroc est considéré comme un constituant éminent de la culture marocaine et ce par sa richesse et son originalité. Cependant il a été longtemps écarté sinon négligé en tant que source d'enrichissement culturel. Mais grâce à la création de l'Institut Royal de la Culture Amazighe (IRCAM), cette lang... | 0 |
Identifying and understanding entities is a central component in knowledge base construction (Roth et al., 2015) and essential for enhancing downstream tasks such as relation extraction *equal contribution Data and code for experiments: https://github. com/MurtyShikhar/Hierarchical-Typing (Yaghoobzadeh et al., 2017b) ,... | 0 |
Current lexical resources such as dictionaries and thesauri do not provide information about the intensity order of words. For example, both WordNet (Miller, 1995) and Roget's 21st Century Thesaurus (thesaurus.com) present acceptable, great, and superb as synonyms of the adjective good. However, a native speaker knows ... | 0 |
Automatically generating a short description for a given image, a problem known as image captioning (Chen et al., 2015) , has drawn extensive attention in both the natural language processing and computer vision community. Inspired by the success of encoder-decoder frameworks with the attention mechanism, previous effo... | 0 |
Recent work on Conditional Random Fields (CRFs) has demonstrated the need for regularisation when applying these models to real-world NLP data sets ( [8] , [9] ). Standard approaches to regularising CRFs, and log-linear models in general, has focused on the use of a Gaussian prior. Typically, for simplicity, this prior... | 0 |
Since the summer of 1993, there has been considerable discussion in the ARPA HLT community of moving the evaluation of understanding systems for both spoken and written language away from application-based metrics (such as correct database response in ATIS, or template fills in MUG) towaxd technology-based metrics. The... | 0 |
Outputs of standard automatic speech recognition (ASR) systems typically consist of utterances where important linguistic and structural information (e.g., true case, sentence boundaries, punctuation symbols, etc) is not available. Such information is crucial in improving the readability of the transcribed speech texts... | 0 |
Aspect-based (also known as aspect-level) sentiment classification aims at identifying the sentiment polarities of aspects explicitly given in sentences. For example, in a comment about a laptop saying "From the speed to the multi-touch gestures this operating system beats Windows easily.", the sentiment polarities for... | 0 |
Pretrained sentence representations have been found useful in various downstream tasks such as visual question answering (Tapaswi et al., 2016) , script inference (Pichotta and Mooney, 2016) , and information retrieval (Le and Mikolov, 2014; Palangi et al., 2016) . Benchmark datasets (Adi et al., 2017; Conneau and Kiel... | 0 |
Controllable text generation has recently become an area of intense focus in the natural language processing (NLP) community. Recent work has focused both on generating text satisfying certain stylistic requirements such as being formal or exhibiting a particular sentiment (Hu et al., 2017; Shen et al., 2017; Ficler an... | 0 |
An often stressed point is that the most widely used classifiers such as Naive Bayes, HMM, and Memory-based Learners are restricted to local decisions only. With grammatical role labeling, for example, there is no way to explicitly express global constraints that, say, the verb "to give" must have 3 arguments of a part... | 0 |
Recently research on the compositional frames (classification and collocafional relationship of words) for Chinese words has been described in Ji et al. (1996) [1] , Ji (1997) [2] . The objective of their work is to obtain the clusters of words of different parts of speech and to derive the coUocational relationship be... | 0 |
In recent years, the possibility to undertake largescale annotation projects with hundreds or thousands of annotators has become a reality thanks to online crowdsourcing methods such as Amazon's Mechanical Turk and Games with a Purpose. Although these techniques open the door to a true revolution for the creation of an... | 0 |
Spoken language understanding (SLU) is a component that understands the user's utterance of a dialogue system. Given an utterance, SLU generates a structured meaning representation of the utterance; i.e., a semantic frame. SLU can be decomposed into several subtasks such as domain identification, intent prediction and ... | 0 |
Knowledge-base question-answering (KBQA) interrogates a knowledge-base (KB) (Yin et al., 2016; Yu et al., 2017; Jin et al., 2019) by interpreting natural-language questions as logical forms (annotations), which can be directly executed on the KB to yield answers (denotations) (Pasupat and Liang, 2016) . KBQA includes s... | 0 |
The automatic processing of textual data generated by NLP software, resulting from Machine Translation, Automatic Speech Recognition or Automatic Text Summarization, raises new challenges for language processing tools. Unlike native texts (texts produced by humans), this new kind of texts is the result of imperfect pro... | 0 |
Community-driven question answering (QA) websites such as Quora, Yahoo-Answers, and Answers.com are accumulating millions of users and hundreds of millions of questions. A large portion of the questions are about facts or trivia. It has been a long pursuit to enable machines to answer such questions automatically.In re... | 0 |
Emotion recognition in conversation (ERC) is a work that recognizes the speaker's emotion and its influencing factors in the process of conversation. Nowadays, social media such as Facebook and Twitter generate a large amount of dialogue data with various modalities of textual, audio, and video all the time. The study ... | 0 |
Neural machine translation (NMT) typically makes use of a recurrent neural network (RNN) -based encoder and decoder, along with an attention mechanism (Bahdanau et al., 2015; Cho et al., 2014; Kalchbrenner and Blunsom, 2013; Sutskever et al., 2014) . However, it has been shown that RNNs require some supervision to lear... | 0 |
This work is part of an effort to develop a robust, domain-independent syntactic parser capable of yielding the unique correct analysis for unrestricted naturally-occurring input. Our goal is to develop a system with performance comparable to extant part-of-speech taggers, returning a syntactic analysis from which pred... | 0 |
Morphological variation is a major contributor to the sparse data problem in NLP, especially for under-resourced languages. The SIGMORPHON 2016 Shared Task (Cotterell et al., 2016) and CoNLL-SIGMORPHON 2017 Shared Task (Cotterell et al., 2017 aimed to inspire researchers to develop better systems for morphological infl... | 0 |
Predicting relevant locations from news articles can result in numerous useful applications. For example, it enables the delivery of news related to a specific city that is of user interest, or facilitates the prediction of a disease outbreak in a specific region when used with event detection techniques.In this paper,... | 0 |
Recently, the NLP community has witnessed a renewed interest in the use of lexical association measures in extracting Multiword Expressions (MWEs).Lexical Association Measures (hereafter, AMs) are mathematical formulas which can be used to capture the degree of connection or association between constituents of a given ... | 0 |
A growing number of natural language processing tools and approaches have been developed for fiction (Agarwal et al., 2013; Bamman et al., 2014; Iyyer et al., 2016; Sims et al., 2019) . These tools generally focus on published literary works, such as collections of novels. We present an NLP pipeline for processing fanf... | 0 |
Abbreviations and acronyms appear frequently in the medical domain. Based on a popular online knowledge base, among the 3,096,346 stored abbreviations, 197,787 records are medical abbreviations, ranked first among all ten domains. 1 An abbreviation can have over 100 possible explanations 2 even within the medical domai... | 0 |
Sumerians lived from prehistoric times until late 3rd millennium BC in lower Mesopotamia (modern Iraq). Sumer was the first highly developed urban civilisation, which used cuneiform script. During the period of the 3rd dynasty of Ur (2100 BC-2000 BC), whose power extended as far as present Iraq and western Iran, the st... | 0 |
Recent years have seen an increasing need for gender-neutral and inclusive language. This need is reflected, among others, by a surge in the use of singular they, 1 currently endorsed as part of APA style as the generic and gender-neutral pronoun. 2 Within the field of Natural Language Processing (NLP), there are vario... | 0 |
Simultaneous Translation aims to translate the speech of a source language into a target language as quickly as possible without interrupting the speaker. Typically, a simultaneous translation system is comprised of an auto-speech-recognition (ASR) model and a machine translation (MT) model. The ASR model transforms th... | 0 |
A central idea from sociolinguistics is that people's social identity is reflected in their use of language, and that people modulate their use of language in order to present particular identities in different situations. The recent availability of social media data has raised interest in confirming and extending thes... | 0 |
This work on text planning is part of a project that is concerned with investigating Dutch prosody by implementing a concept-to-speech system. The project focuses on the prosodic module, which predicts the pitch accents and the prosodic boundaries of an utterance on the basis •of its semantic and syntactic •structure a... | 0 |
There is a growing need to index, search, summarize and otherwise process the increasing amount of available broadcast news, broadcast conversations, meetings, class lectures, and telephone conversations. While it is clear that users have wide ranging goals in the context of information retrieval, we assume that some w... | 0 |
The ability to make context-sensitive translation decisions is one of the major strengths of phrasebased SMT (PSMT). However, the way PSMT exploits source-language context has several limitations as pointed out, for instance, by Quirk and Menezes (2006) and Durrani et al. (2013) . First, the amount of context used to t... | 0 |
Many natural language processing (NLP) problems involve graph construction. Examples include constructing polarity lexicons based on lexical graphs from WordNet (Rao and Ravichandran, 2009) , constructing polarity lexicons from web data (Velikovich et al., 2010) and unsupervised part-ofspeech tagging using label propag... | 0 |
The task of implicit discourse relation recognition is to identify the type of discourse relation (a.k.a. rhetorical relation) hold between two spans of text, where there is no discourse connective (a.k.a. discourse marker, e.g., but, and) in context to explicitly mark their discourse relation (e.g., Contrast or Explan... | 0 |
Representing world knowledge that can be used for commonsense reasoning is a long-standing AI goal. Scripts (Schank and Abelson, 1977) are structured knowledge representations capturing the relationships between prototypical event sequences and their participants in a given scenario. For example, given the event "John ... | 0 |
The parsing of noun phrases (NPs) involves the same difficulties as parsing in general. NPs contain structural ambiguities, just as other constituent types do, and resolving these ambiguities is required for their proper interpretation. Despite this, statistical methods for parsing NPs have not achieved high performanc... | 0 |
The appropriate treatment of proper names is essential in a natural language understanding system which processes unedited newswire text, since up to 10 % of this type of text may consist of proper names (Coates-Stephens, 1992) . Nor is it only the sheer volume of names that makes them important; for some applications,... | 0 |
Persuasion aims to use conversational and messaging strategies to change one specific person's attitude or behavior. Moreover, personalized persuasion combines both strategies and user information related to the outcome of interest to achieve better persuasion results (Kreuter et al., 1999; Rimer and Kreuter, 2006) . S... | 0 |
Traditionally researchers have defined the problem of comprehending anaphoric expressions as one of determining the antecedent of an anaphoric expression, that is, determining to which word or phrase an anaphoric expression refers or "points". Recent studies in both artificial intelligence and linguistics have demonstr... | 0 |
In general, causality refers to the way of knowing whether one state of affairs is causally related to another. 1 Within linguistics, causality has long been established as a central phenomenon for investigation. In this paper, we look at causality from the perspective of a research question from political science, whe... | 0 |
Although Abstract Meaning Representation (AMR) (Banarescu et al., 2013) shows promise for a range of tasks such as summarization (Liu et al., 2015; Viet et al., 2017) and information extraction (Garg et al., 2016) , it is restricted to capturing the semantics of individual sentences. For many purposes, when examining t... | 0 |
A key challenge in machine reading (Etzioni et al., 2006) is to identify the entities mentioned in text, and associate them with appropriate background information such as their type. Consider the sentence "Some people think that pineapple juice is good for vitamin C." To analyze this sentence, a machine should know th... | 0 |
Statistical machine translation (SMT) systems require large parallel corpora in order to be able to obtain a reasonable translation quality. In statistical learning theory, it is assumed that the training and test datasets are drawn from the same distribution, or in other words, they are from the same domain. However, ... | 0 |
Joint entity and relation extraction intend to simultaneously extract entity and relation facts in the given text to form relational triples as (s, r, o) . The extracted information provides a supplement to many studies, such as knowledge graph construction (Riedel et al., 2013) , question * * Corresponding author.answ... | 0 |
Recent developments on pretrained contextualized embeddings have significantly improved the performance of structured prediction tasks in natural language processing. Approaches based on contextualized embeddings, such as ELMo (Peters et al., 2018) , Flair (Akbik et al., 2018) , BERT (Devlin et al., 2019) , and XLM-R (... | 0 |
Phonological processes govern the way speech sounds in natural languages change depending on the context. For example, in English verbs, the past tense suffix /d/ turns into [t] after voiceless consonants (so the word "zipped" is pronounced [zIpt], while "begged" is pronounced [bEgd] ). Linguists routinely face the tas... | 0 |
Question answering (QA) systems use reader and retriever models to learn and parse information from knowledge bases such as Wikipedia. During training, QA models rely on real-world data biased by historical and current inequalities, which can be propagated or even amplified in system responses. For example, historical ... | 0 |
A series of countries from our world are multilingual, which implies that there are multiple languages spoken by their population. People tend to mix them at the phrase or sentence level in order to express ideas with ease, thus creating a phenomenon called code-mixing or code-switching. As it is expected, this embeddi... | 0 |
The classical referring expression generation (REG) problem intends to determine a noun phrase which univocally identify an object in a collection. From a knowledge representation perspective, the problem is to determine (if possible) a collection of object properties that can be employed in the noun phrase for the abo... | 0 |
As a tool for automated assessment, short answer questions reveal cognitive processes and states in students that are difficult to uncover in multiplechoice equivalents (Nicol, 2007) . Even when it seems that items could be designed to address the same cognitive construct, success in devising multiple-choice and short ... | 0 |
Machine Translation (MT) has been evolving in recent years achieving successful translations as shown by international evaluations such as WMT 1 and increasing use of MT in commercial applications. However, specific domains like legal, biomedical, etc., still lag behind the state-of-the-art MT systems. This can mostly ... | 0 |
System combination merges the output of several machine translation systems into a single improved output. Our system combination scheme, submitted to the Workshop on Statistical Machine Translation (WMT) 2010 as cmu-heafield-combo, is an improvement over our previous system (Heafield et al., 2009) , called cmu-combo i... | 0 |
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