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The Neogrammarians (Osthoff and Brugmann, 1878) formalised one of the main hypotheses of the then recent field of comparative linguistics, the regularity of sound changes: if a phone in a word, at a given moment in the history of a given language, evolves into another phone, then all occurrences of the same phone in th... | 0 |
Ces dernières années, les blogs ont conquis leur place à côté des médias traditionnels et deviennent une source d'informations incontournable. Les blogueurs l'utilisent majoritairement à des fins d'auto-représentation, et la plupart se forment autour des affects ou des idées propres à leur auteur. Le blog est souvent c... | 0 |
Neural Machine Translation (NMT) is progressing at a rapid pace. Since the introduction of the first encoder-decoder architecture (Sutskever et al., 2014; Cho et al., 2014) , then completed with an attention mechanism (Bahdanau et al., 2015; Vaswani et al., 2017) , the performance of NMT systems is now good enough for ... | 0 |
Consider a simple case of ambiguous anaphoric reference: (1) I had gone to see John before I visited Bill and Mary. He doesn't want to speak with her.What can we say about the resolution of the anaphora? The pronoun her probably refers to Mary; the pronoun he is ambiguous between John and Bill, but most likely refers t... | 0 |
Lexical entailment (LE) refers to the hyponymy-hypernymy relation, also known as TYPE-OF, or IS-A, which is a fundamental asymmetric lexical relation (Vulić et al., 2017) . It is a basic requirement for tasks like Question Answering (QA) and Recognizing Textual Entailment (RTE). And more general reasoning over cross-li... | 0 |
This poster presents a pilot study for a new interdisciplinary project which aims at creating an automated, time-aligned and language-based access to large archives of audiovisual documents. The idea is to facilitate the work of researchers who wish to pinpoint particular segments of AV material without having to brows... | 0 |
The current dominant approach to learning sentence embeddings is fine-tuning general-purpose pretrained language models, such as BERT (Devlin et al., 2019) , with a particular training supervision. The type of supervision can be natural language inference data (Reimers and Gurevych, 2019) , adjacent sentences (Yang et ... | 0 |
Code-switching is a phenomenon that occurs in multilingual societies wherein speakers who are fluent in two or more languages switch between these languages in the same conversation or an utterance. Code-switching is a challenging problem for speech and natural language processing systems to handle due to the lack of m... | 0 |
Though speech has long served as a basic method of human communication, revisiting and browsing speech content had never been a possibility before human can record their own voice. Recent technological advances in recording, compressing, and distributing such archives have led to the consistently increasing availabilit... | 0 |
Attention-based models have become architectures of choice for many NLP tasks. In addition to significant performance gains, these models are attractive, as attention is often used as a proxy for human interpretable rationales. Their success, however, is conditioned on access to large amounts of training data. To make ... | 0 |
The Hindi Belt or Hindi heartland, is a linguistic region consisting of parts of India where Hindi and its various dialects are spoken widely (Sukhwal, 1985) . Hindi as a language has evolved over the years due to migration and invasion of various socio-ethnic groups like Turks, Britishers etc. This has given it a dyna... | 0 |
In the current wireless era, cellular phones have become daily-life necessities. People carry their own handsets and make phone calls anytime, everywhere, while public payphones have almost disappeared. Inspired by this vast number of mobile phone users, the wireless communication industry is developing wireless data s... | 0 |
In order to avoid unnecessary repetitions and redundancy, speakers can use a wide variety of expressions when referring to the same entity or event in the world. Languages usually offer several lexical and grammatical tools for this purpose. One of the grammatical tools to express identity is coreference, which is used... | 0 |
Understanding written language is a non-trivial task. It takes years for children to read, and ambiguities of written communication remain long after we learn the basics. Despite these apparent complexities, the bag-of-words (BOW) approach, which ignores structure both within a sentence and within a document, continues... | 0 |
Natural Language Inference (NLI) is an important topic in the Artificial Intelligence (AI) field, and any NLI related issue can be checked by asking an appropriate corresponding question (Chen, 2018) . Therefore, the Question Answering (QA) task has become a very suitable testbed for evaluating NLI models and checking ... | 0 |
Natural language representation in continuous vector space has been successfully used in many NLP tasks (Al-Rfou et al., 2013; Bansal et al., 2014; Bowman et al., 2014; Boyd-Graber et al., 2012; Chen and Rudnicky, 2014; Guo et al., 2014; Iyyer et al., 2014; Levy and Goldberg, 2014; Mikolov et al., 2013c) . Previous res... | 0 |
Pre-trained language models (Peters et al., 2018; Radford et al., 2019; Devlin et al., 2019; Liu et al., 2019b) give competitive results on a variety of NLP tasks (Zhou and Zhao, 2019; Joshi et al., 2019; Liu and Lapata, 2019; Cui et al., 2020) . It has been shown that they can effectively capture syntactic features (G... | 0 |
Much of the current NLP research focuses on a handful of world languages (e.g., English, French, Spanish etc.). They enjoy substantially larger computational linguistic resources as compared to their low-resource counterparts (e.g., Bengali, Odia etc.). However, in the midst of global-scale events like the ongoing COVI... | 0 |
For the purposes of this paper, a multilingual text means one containing text segments, limited to those longer than a clause, written in different languages. We can often find such texts in linguistic resources collected from the World Wide Web for many nonmajor languages, which tend to also contain portions of text i... | 0 |
This paper presents a web-based tool for visualization of machine translation quality estimation (QE) (Specia et al, 2018) results. The tool allows users to submit one or several bilingual files with machine translation (MT) output and see information about its estimated quality, namely the predicted post-editing dista... | 0 |
Temiar is an Austroasiatic language of the Mon-Khmer group spoken by a variety of tribal people in West Malaysia (Benjamin, 1976) . Its intricate morphological system has received some attention in the theoretical literature. The main focus has been on the aspectual morphology of verbs, where an interesting pattern of ... | 0 |
Reranking is the process of rescoring an n-best list with an external model, and it is an effective method for improving performance in NLP tasks. In parsing, rerankers are able to incorporate arbitrary global features from the entire parse tree that would be intractable in a base parser. More informative features can ... | 0 |
Language is one of the most important aspects of human intelligence; it allows humans to coordinate and share knowledge with each other. We will want artificial agents to understand language as it is a natural means for us to specify their goals.So how can we train agents to understand language? We adopt the functional... | 0 |
The prevalence of diabetes is increasing in the US, mounting to 30.3 million cases in 2015, of whom 7.2 million were undiagnosed (Centers for Disease Control and Prevention, 2017) . Diabetes caused over 79 thousand US deaths in 2015, in addition to $245 billion in economic costs in 2012 (American Diabetes Association, ... | 0 |
Most existing semantic parsing efforts employ a CKYstyle bottom-up parsing strategy to generate a meaning representation in simply typed lambda calculus (Zettlemoyer and Collins, 2005; Lu and Ng, 2011) or its variants (Wong and Mooney, 2007; Liang et al., 2011) . Although these works led to fairly accurate semantic par... | 0 |
Recently, interest has grown in the task of automatic question generation (AQG) from text (Sun et al., 2018; Kumar and Black, 2020) . AQG is useful in building conversational AI systems (Bordes et al., 2017; Gao et al., 2019) , generating synthetic examples for QA (Alberti et al., 2019; Dong et al., 2019; Sultan et al.... | 0 |
Distributional models of lexical semantics, which assume that aspects of a word's meaning can be related to the contexts in which that word is typically used, have a long history in Natural Language Processing (Spärck Jones, 1964; Harper, 1965) . Such models still constitute one of the most popular approaches to lexica... | 0 |
Recently, sequence-to-sequence models have achieved remarkable performance in various natural language processing tasks, including semantic parsing (Dong and Lapata, 2016; Jia and Liang, 2016; Konstas et al., 2017; Dong and Lapata, 2018) , the task of mapping natural language to formal meaning representations ( Figure ... | 0 |
As the pace of scientific publication continues to increase, Natural Language Processing (NLP) tools that help users to search, discover and understand the scientific literature have become critical. In recent years, substantial improvements in NLP tools have been brought about by pretrained neural language models (LMs... | 0 |
In recent years, vector space models (VSMs) have been proved successful in solving various NLP tasks including named entity recognition, part-of-speech tagging, parsing, semantic rolelabeling and answering synonym or analogy questions (Turney et al., 2010; Collobert et al., 2011) . Also, VSMs are reported performing we... | 0 |
Estimating the degree of semantic similarity between two sentences is the building block of many Natural Language Processing (NLP) applications, such as question answering, textual entailment, text summarization etc. Therefore, Semantic Textual Similarity (STS) has received an increasing amount of attention in recent y... | 0 |
There has been considerable research for coreference annotation on various languages (English (Hovy et al., 2006) , French (Mitkov et al., 2000) , Spanish (Recasens et al., 2007) , Czech (Nedoluzhko et al., 2013) , etc), on diverse domains like newspaper texts, bio-medical journals, etc.Coreference annotation is a time... | 0 |
Machine Reading Comprehension (MRC) is a central task in natural language understanding (NLU) with many applications, such as information retrieval and dialogue generation. Given a query and a text paragraph, MRC extracts the span of the correct answer from the paragraph. Recently, as a series of largescale annotated d... | 0 |
Dementia is a syndrome primarily presenting with broad cognitive impairments. There are multiple underlying causes that result in dementia such as Alzheimer's Disease (AD) or fronto-temporal lobar degeneration or focal lesions (MacPherson et al., 2016) . These sub-forms have different neurocognitive profiles. The most-... | 0 |
Visual dialogue is the task of holding natural, often goal-oriented conversation in a visual context (Das et al., 2017a; De Vries et al., 2017) . This typically involves two types of advanced grounding: symbol grounding (Harnad, 1990) , which bridges symbolic natural language and continuous visual perception, and commo... | 0 |
Transliteration is defined as phonetic translation of names across languages. Transliteration of Named Entities is necessary in many applications, such as machine translation, corpus alignment, cross-language information retrieval, information extraction and automatic lexicon acquisition.The transliteration modeling ap... | 0 |
The extreme type sparsity in text in a morphologically rich language, i.e., a language which relies strongly on changes in the surface form of words to express properties like gender, tense or number, requires natural language processing (NLP) systems which are able to handle inflected words in a systematic way. The SI... | 0 |
Generating fluent natural language responses from structured semantic representations is a critical step in task-oriented conversational systems. With their end-to-end trainability, neural approaches to natural language generation (NNLG), particularly sequence-to-sequence (Seq2Seq) models, have been promoted with great... | 0 |
Automatic summarisation is the task of reducing a document to its main points. There are two streams of summarisation approaches: extractive summarisation, which copies parts of a document (often whole sentences) to form a summary, and abstractive summarisation, which reads a document and then generates a summary from ... | 0 |
The rise of Transformer-based language models (TLMs) powered by multi-head self-attention (Vaswani et al., 2017) has been accompanied by impressive performance gains in virtually all areas of NLP. When pre-trained on massive datasets on the order of billions of words, models like GPT-2 (Radford et al., 2019) , BERT (De... | 0 |
The Universal Dependencies (UD) project Nivre et al., 2016 ) is a multilingual annotation scheme for dependency grammars that has gained wide usage (Zeman et al., 2017; Kong et al., 2017; Qi et al., 2020) . To this extent, automatically identifying whether a dependency parse 1 is correct or incorrect, as well as the po... | 0 |
Time is an important dimension when we describe the world because many facts are time-sensitive, e.g., one's place of residence, one's employment, or the progress of a conflict between countries. Consequently, many applications can benefit from temporal understanding in natural language, e.g., timeline construction Min... | 0 |
Two workshops on Cross-Framework Meaning Representation Parsing (MRP) hosted by the 2019 and 2020 editions of the Conference on Computational Natural Language Learning (CoNLL), featured two editions of a shared task, where implementations of parsers turning raw text into different flavors of meaning representation grap... | 0 |
An important source of ambiguity that must be resolved by any natural language understanding system is the mapping between syntactic dependents of a predicate and the semantic roles 1 that they each express. The ambiguity stems from the fact that each predicate can allow several alternate mappings, or linkings, 2 betwe... | 0 |
One of the key indicators of scientific writing is the quantities description of various experiments and results. While the mentions of all measurements could provide a rigorous understanding of the topic, it might make the reading and automatic processing of the text more difficult. As such, designing effective method... | 0 |
In recent year, machine learning methods have significantly contributed to the development of automatic speech recognition (ASR) (Deng and Li, 2013; Padmanabhan and Johnson Premkumar, 2015; Benkerzaz et al., 2019; Nassif et al., 2019) . The fast advances in the ASR field can be explained by the urgent need of efficient... | 0 |
Automatic semantic annotation and analysis is an important task for Natural Language Processing (NLP), and semantic taggers have been developed and used for carrying out semantic analysis of language data on a large scale. A major tool built for such a purpose is USAS (UCREL Semantic Analysis System) 1 (Rayson et al., ... | 0 |
Translation memories (TMs) are nowadays an indispensable tool for translators. First-generation TMs retrieve similar sentences from a database of already translated examples and provide the translator with the translation of the most similar sentence for minimal edition to obtain a relevant translation. Secondgeneratio... | 0 |
In languages with irregular spelling systems, such as English, most speakers have trouble spelling at least some words. To aid spelling there are orthographic dictionaries (which index words by their sequence of letters) and phonemic dictionaries (which index words by their sequence of phonemes). We will be looking at ... | 0 |
Idiomatic expressions are abundant in natural language. They also often behave idiosyncratically and are therefore a significant challenge for natural language processing systems. For example, idioms can violate selectional restrictions (as in push one's luck), disobey typical subcategorisation constraints (e.g., in li... | 0 |
Neural machine translation (NMT) is a wellestablished approach that yields the best results on most language pairs (Bojar et al., 2016; Cettolo et al., 2016) . Most systems are based on the sequence-to-sequence model with attention (Bahdanau et al., 2015) which employs single-layer recurrent neural networks both in the... | 0 |
The joint parsing of syntactic and semantic dependencies introduced by the shared task of CoNLL-08 is more complicated than syntactic dependency parsing or semantic role labeling alone (Surdeanu et al., 2008) . For semantic parsing, in particular, a dependency-based representation is given but the predicates involved a... | 0 |
Text classification, named entity recognition (NER), and medical concept normalization (MCN) in freeform texts are crucial steps in every text-mining pipeline. Here we focus on discovering adverse drug reaction (ADR) concepts in Twitter messages as part of the Social Media Mining for Health (SMM4H) 2020 shared tasks (K... | 0 |
Les disfluences sont un phénomène apparaissant fréquemment dans toute production orale spontanée. Elles ont donné lieu à de nombreuses études, que ce soit dans le domaine du Traitement Automatique de la Parole, ou celui du Traitement Automatique du Langage Naturel. En effet, leur étude et leur identification précise es... | 0 |
The World Wide Web contains a huge number of on-line documents that are easily accessible. Finding information relevant to user needs has become increasingly important. The most important information on the Web is usually contained in the text. We obtain a huge number of review documents that include user's opinions fo... | 0 |
Despite recent increases in the availability of machine learning methods, extracting structured information from large amounts of unstructured and noisy clinical documents, as available in electronic health record (EHR) systems, is still a challenging task. Patient's EHR are filled with clinical concepts, often misspel... | 0 |
We report on our efforts on the IWSLT 2018 Speech Translation task. The goal of the 2018 task is to build and evaluate English-to-German speech translation systems on the domain of lectures and TED talks. We build two systems:• Pipeline System: English (EN) speech transcription system using a joint CTC-attention model ... | 0 |
Telugu is morphologically rich and follows different grammatical structures compared to western languages such as English and Spanish. However, to maintain compatibility, the western ideology of rules are adopted in current approaches. Thus, many ideas and significant information of the language is lost. Indian languag... | 0 |
Language service providers (LSP) and human professional translators currently use machine translation (MT) technology as a tool to increase their productivity. For this, MT is closely integrated into computer-assisted translation (CAT) tool. The MT system suggests an automatic translation of the input sentence which is... | 0 |
Nous nous intéressons dans cet article au processus de segmentation de textes en chunks, c'est-à-dire en constituants continus non-récursifs (Abney, 1991) . La tâche de chunking vise en effet à identifier la structure syntaxique superficielle d'un énoncé, c'est-à-dire à reconnaître ses constituants minimaux, sans pour ... | 0 |
Named Entity Recognition (NER) is the task of detecting mentions from text and classifying them into predefined types. It is a fundamental task in the field of natural language processing (NLP), which can facilitate many other tasks, such as entity linking (Fang et al., 2020) , machine translation (Gekhman et al., 2020... | 0 |
The development of natural language processing tools for information extraction or document summarization tailored to scientific literature will provide quick tracking of scientific creativity and innovation. Easy access to challenges faced by the researchers, their results and contributions, and how these relate to th... | 0 |
Current statistical machine translation (SMT) systems are mostly sentence-based. The major drawback of such a sentence-based translation fashion is the neglect of inter-sentential dependencies. As a linguistic means to establish inter-sentential links, lexical cohesion ties sentences together into a meaningfully interw... | 0 |
Biologists believe that they know what genes, organisms, chemical compounds, and diseases are. Linguists believe that they know what nouns, verbs, and clauses are. Ordinary literate speakers of English believe that they know what people, places, and organizations are. And all of them believe that they can recognize and... | 0 |
The ecological validity (de Vries et al., 2020) of data-to-text tasks requires that tasks resemble, as closely as possible, real-world problems. Only if this is the case can neural data-to-text solutions be operationally deployed with confidence. In the context of data-to-text, one of the issues with ecological validit... | 0 |
Humans are able to do common sense reasoning across a variety of modalities -textual, visual and for a variety of tasks -reasoning, locating, navigation. Several such tasks require spatial knowledge understanding and reasoning (Kordjamshidi et al., 2010) , (Kordjamshidi et al., 2011) , (Johnson et al., 2017) , (Wang et... | 0 |
It is well known how to efficiently minimize a deterministic finite-state automaton (DFA), in the sense of constructing another DFA that recognizes the same language as the original but with as few states as possible (Aho et al., 1974) . This DFA also has as few arcs as possible.Minimization is useful for saving memory... | 0 |
Photographs have emerged as a means for sharing information, effective storytelling, preserving memories, and brand marketing among many other applications. The advent of photo-centric social media platforms such as Instagram, Snapchat, etc. along with easy access to high quality photo-taking devices has only made phot... | 0 |
We advocate researching unsupervised techniques for Word Sense Disambiguation (WSD). Supervised techniques offer better results in general but the setbacks, such as the problem of developing reliable training data, are very considerable. Also there's probably more to WSD than blind machine learning (a typical approach,... | 0 |
The question of distance between languages, and comparison of possible definitions, has relatively less consideration in the literature than other language issues, with notable exceptions being (Berstel, 1973) and (Salomaa and Soittola, 1978) . This may seem surprising, considering that the current digital climate nece... | 0 |
Many approaches to joint word segmentation and POS tagging can be interpreted as reranking with a word lattice (Jiang et al., 2008) , wherein a small lattice is generated for an input sentence, and then the lattice paths are reranked to obtain the optimal one. Examples of such a method include (Asahara and Matsumoto, 2... | 0 |
Relation extraction is a crucial task in the field of natural language processing (NLP). It has a wide range of applications including information retrieval, question answering, and knowledge base completion. The goal of relation extraction system is to predict relation between entity pair in a sentence (Zelenko et al.... | 0 |
Predicting whether a given word, sentence or document expresses a positive, neutral or negative sentiment is a fundamental task in Natural Language Processing (NLP). For instance, a recent survey of text mining papers from 1992-2017 has found that out of 4, 346 papers, 467 had a sentiment analysis component (Liu et al.... | 0 |
Several studies have been successful in representing the meaning of a word with a vector in a continuous vector space (e.g., Mikolov et al. 2013a; Pennington et al. 2014) . These representations are useful for a range of natural language processing (NLP) tasks. The interpretation and geometry of the word embeddings hav... | 0 |
Distributed word representations, or word embeddings, have been successfully used in many NLP applications (Turian et al., 2010; Collobert et al., 2011; . Traditionally, word representations have been obtained using count-based methods (Baroni et al., 2014) , where the co-occurrence matrix is derived directly from corp... | 0 |
In the ever-growing field of translation metrics, a number of systems exist which attempt to provide an overall rating for a sentence. Most of these use one or more reference translations produced by a human as a gold standard. One of the earliest examples of such a metric may be BLEU (Papineni et al., 2002) , using an... | 0 |
Word representations learned from neural language models have been shown to improve many NLP tasks, such as part-of-speech tagging (Collobert et al., 2011) , dependency parsing (Chen and Manning, 2014; Kong et al., 2014) and machine translation Kalchbrenner and Blunsom, 2013; Devlin et al., 2014; Sutskever et al., 2014... | 0 |
Though Transformer (Vaswani et al., 2017) has promoted conventional autoregressive generation (AR) by leveraging multi-head self-attention to avoid recurrence at training, decoders that generate each token conditioned on previously generated tokens still make it impossible to take full advantage of parallelism during i... | 0 |
A fairly novel area of retrieval called topic detection and tracking (TDT) attempts to design methods to automatically (1) spot new, previously unreported events, and (2) follow the progress of the previously spotted events (Allan et al., 1998c; Yang et al., 1998) .Our contribution deals with three problems in TDT. Fir... | 0 |
Kernel methods are considered the most effective techniques for various relation extraction (RE) tasks on both general (e.g. newspaper text) and specialized (e.g. biomedical text) domains. In particular, as the importance of syntactic structures for deriving the relationships between entities in text has been growing, ... | 0 |
Humans can learn a new word quickly from minimal exposure to its context, as in the following example:The Labrador runs happily towards me, barking and wagging its tail.Even this is the first time one hears about Labrador, we can guess it should be an animal or even further a dog easily, since it runs, barks and has a ... | 0 |
Opinion, one of the main factors shaping human behavior, is crucial to our daily activities (Liu, 2012) . Every choice we make in our life, ranging from where to go for a Friday dinner to which job offer to pick up, is largely influenced by what other people think. To help individuals navigate decision-making processes... | 0 |
Machine translation is urgently needed to get away with the language barrier between different nations. The task of machine translation is to realize mapping from one language to another. At present there are three main methods for machine translation systems : 1) pattern/rule based systems: production rules compose th... | 0 |
Semantic similarity is an essential component of many applications in Natural Language Processing (NLP). Previous works often focus on text semantic similarity on the same level, i.e., paragraph to paragraph or sentence to sentence, and many effective text semantic measurements have been proposed (Islam and Inkpen, 200... | 0 |
One strand of work in dialog research targets the rapid prototyping of virtual humans capable of conducting a conversation with humans in the context of a virtual world. In particular, question answering (QA) characters can respond to a restricted set of topics after training on a set of dialogs whose utterances are an... | 0 |
Neural network architectures such as Transformers (Vaswani et al., 2017; Dehghani et al., 2018) and attention networks (Parikh et al., 2016; Seo et al., 2016; Bahdanau et al., 2014) are dominant solutions in natural language processing (NLP) research today. Many of these architectures are primarily concerned with learn... | 0 |
Abstract Meaning Representations (AMRs) (Banarescu et al., 2013) model sentence level semantics as rooted, directed, acyclic graphs. Nodes in the graph are concepts which represent the events, objects and features of the input sentence, and edges between nodes represent semantic relations. AMR introduces re-entrance re... | 0 |
Occurrences of events, referring to changes and actions, show regularities. Specifically, certain events often co-occur and in a particular temporal order. For example, people often go to work after graduation with a degree. Such "before/after" temporal event knowledge can be used to recognize temporal relations betwee... | 0 |
Shallow discourse parsing aims to automatically identify discourse relations (e.g., comparisons) between adjacent sentences. When connectives such as however explicitly appear, discourse relations are relatively easy to classify, as connectives provide strong cues (Pitler et al., 2008) . In contrast, it remains challen... | 0 |
The success and widespread adoption of probabilistic models in NLP has led to numerous variant methods for any given task, and it can be difficult to tell what aspects of a system have led to its relative successes or failures. As an example, maximum entropy taggers have achieved very good performance (Ratnaparkhi, 199... | 0 |
Machine translation (MT) between closely related languages has been paid attention in more than the last twenty years by researchers from many countries. Intuitively, this kind of machine translation should be easier than MT between distant languages since it is possible to exploit the similarity at various linguistic ... | 0 |
Extracting data elements such as study descriptors from publication full texts is an essential step in a number of tasks including systematic review preparation (Jonnalagadda et al., 2015) , construction of reference databases (Kleinstreuer et al., 2016) , and knowledge discovery (Smalheiser, 2012) . These tasks typica... | 0 |
Several machine learning algorithms such as Support Vector Machines (SVMs) and boosting-based learning algorithms have been applied to Natural Language Processing (NLP) problems successfully. The cases of boosting include text categorization [11] , POS tagging [5] and text chunking [7, 5] , and so on. Furthermore, pars... | 0 |
Machine translation (MT) has benefited a lot from the advancement of automatic evaluation in the past decade. To a certain degree, its progress is also confined to the limitations of evaluation metrics in use. Most efforts devoted to evaluate the quality of MT output so far have still focused on the sentence level with... | 0 |
Spoken language understanding is a core problem in task oriented dialog systems with the goal of understanding and formalizing the intent expressed by an utterance (Tur and De Mori, 2011) . It is often modeled as intent classification (IC), an utterance-level multi-class classification problem, and slot labeling (SL), ... | 0 |
This paper proposes a method for integrating example-based and rule-based machine translation systems with statistical methods. It extends a greedy decoder for statistical machine translation (cf. Section 2), which searches for an optimal translation by using SMT models starting from a decoder seed, i.e., the source la... | 0 |
Inferring characteristics of an author by automatically analyzing that author's texts is a task that is increasingly drawing attention in recent years. Traits such as gender, age, level of education or native language are some of the properties targeted thus far (e.g., Koppel et al., 2005; Estival et al., 2007; Wong an... | 0 |
The TempEval shared tasks have, since 2007, provided a focus for research on temporal information extraction (Verhagen et al., 2007; Verhagen et al., 2010; UzZaman et al., 2013) . Participant systems compete to identify critical components of the timeline of a text, including time expressions, event expressions and tem... | 0 |
Conversation modeling has been a long interest of natural language research. Recent approaches for data-driven conversation modeling mostly build upon recurrent neural networks (RNNs) (Vinyals and Le, 2015; Sordoni et al., 2015b; Shang et al., 2015; Li et al., 2017; . use a hierarchical RNN structure to model the conte... | 0 |
Pretrained language models are getting bigger and so does their capacity to memorize data from the training phase (Carlini et al., 2021) . A rising concern regarding these models is "data contamination"-when downstream test sets find their way into the pretrain corpus. For instance, Dodge et al. (2021) examined five be... | 0 |
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