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We study news event detection from Twitter messages (tweets). Generally, tweets can be classified into three groups: 1) news events, or breaking news such as "Manchester united Vs Athletic in Jan. 1st"; 2) hot topics that spread among a large amount of Twitter users, such as horoscope topics (e.g. "You have recently ex... | 0 |
Topic models have been widely used for discovering hidden themes from a large collection of documents in an unsupervised manner. Recently, to avoid the complex and specific inference process of graph model-based method such as LDA (Blei et al., 2003) , neural topic modeling that utilizes neural-network-based black-box ... | 0 |
As statistical language learning technologies strain the limits of the relatively flat, simplistic structures of first-generation models, the need to incorporate representations that capture meaningful semantic patterns has become increasingly evident. Particularly for cross-lingual applications, techniques for multili... | 0 |
This paper details a system demonstration for the 2018 Trolling, Aggression and Cyberbullying shared task (Kumar et al., 2018) . The challenge was to provide a system capable of predicting the true class of a social media post which would be either one of (i) Non-Aggression (NOAG), (ii) Covert Aggression (CAG), or (iii... | 0 |
Abusive language is a broad term encompassing several linguistic patterns linked to phenomena such as offensive language, aggressive language or hate speech. Abusive language is a strong signal to detect problematic use of languages, e.g., in cases of cyberbullying, misogyny, racism, or trolling. Aggressive language is... | 0 |
In studies on the Japanese grammar, those lexemes (words) that form a phrasal verb in combination with the light verb SURU 1 'do' have been referred to as verbal nouns (VNs) (Martin 1988 , Kageyama 1993 , Uchida and Nakayama 1993 .(Lexemes that may function as) a VN typically may function as a regular noun and serve as... | 0 |
Multiword expressions (MWEs) are phraseological units, which consist of more than one lexeme and exhibit some kind of idiosyncrasy (Sag et al., 2002) ; such idiosyncrasy may be lexical (ad hoc), syntactic (by and large), semantic (middle of the road), pragmatic (all aboard), or statistical (black and white but not whit... | 0 |
FBK's participation to the news translations shared task in WMT 17 focused this year on the English-German language direction. Our purpose was to explore the state of the art and build a competitive neural machine translation [3] system in order to gain a practical knowledge of the available tools. With respect to our ... | 0 |
Pre-trained language models (PrLMs) such as BERT and its variants (Liu et al., 2019c; Yang et al., 2019) have shown significant success for various downstream NLP tasks. However, these deep neural networks are sensitive to different cross-domain distributions (Quionero-Candela et al., 2009) and their effectiveness will... | 0 |
Code Mixing is a natural phenomenon of embedding linguistic units such as phrases, words or morphemes of one language into an utterance of another (Muysken, 2000; Duran, 1994; Gysels, 1992) . Code-mixing is widely observed in multilingual societies like India, which has 22 official languages most popular of which are H... | 0 |
Topic models such as Latent Dirichlet Allocation or LDA (Blei et al., 2003) are widely used to capture hidden topics in a corpus. When we have domain knowledge of a target corpus, incorporating the knowledge into topic models would be useful in a practical sense. Thus there have been many studies of semi-supervised ext... | 0 |
DATR was introduced by Evans and Gazdar (1989a; 1989b) as a simple, declarative language for representing lexical knowledge in terms of path/value equations. The language lacks many of the constructs found in general purpose, knowledge representation formalisms, yet it has sufficient expressive power to capture concise... | 0 |
A problem of recognizing textual entailments (RTE)-given two text fragments T (for a text) and H (for a hypothesis), determine whether T entails, contradicts or is neutral to H-is considered as a complex and, at the same time, fundamental problem for several NLP tasks (Dagan et al., 2005) . For more than a decade, RTE ... | 0 |
Hyper-partisan refers to a person or a group's tendency to be extremely partisan or biased towards a person or a group and specifically towards a political person or a political party. With the tremendous increase in citizen-based journalism, where anyone can create a website and post his (biased) views, there is a new... | 0 |
In text summarization, manual evaluation, as exemplified by the Pyramid method (Nenkova and Passonneau, 2004) , is the gold-standard in evaluation. However, due to time required and relatively high cost of annotation, the great majority of research papers on summarization use exclusively automatic evaluation metrics, s... | 0 |
Information retrieval, summarization, and online advertising rely on identifying the most important words and phrases in web documents. While traditional techniques treat documents as collections of keywords, many NLP systems are shifting toward understanding documents in terms of entities. Accordingly, we need new alg... | 0 |
Retrieval-based methods (Gu et al., 2018; Bapna and Firat, 2019; Khandelwal et al., 2020a) are increasingly receiving attentions from the machine translation (MT) community recently. These approaches complement advanced neural machine translation (NMT) models (Sutskever et al., 2014; Bahdanau et al., 2015; Vaswani et a... | 0 |
Discourse is defined as a coherent, structured group of sentences (Jurafsky and Martin, 2009) . Discourse parsing enables the creation of models for further downstream natural language processing tasks such as question-answering, text summarization, information retrieval and extraction, sentiment analysis, and argument... | 0 |
BERT (Devlin et al., 2019 ) is a high-performance pre-training model. It helped in the improvement of the performance of natural language processing tasks. Generally, task-based approaches were adopted for evaluating pre-training models like BERT. In English language, a dataset for task-based evaluation, such as the ge... | 0 |
For effective processing of text, tools at different conceptual levels, say from letter/syllable level to discourse level are needed. Output of these tools can then be used in different NLP based applications, beginning with simple spell checkers to sophisticated machine translation systems. These tools could be comple... | 0 |
Using parallel data for Word Sense Disambiguation (WSD) is as old as Statistical Machine Translation (SMT): Brown et al. (1992) analyze texts in both languages before the IBM SMT models are trained and used, including WSD driven purely by translation equivalents. 1 A combination of parallel texts and lexicons also prov... | 0 |
During recent years there has been an increased interest to use corpus-driven approaches to acquire high quality semantic lexicons on large scale: (Grefenstette (1994) ; Dorr & Jones (1996) ; Hearst and Schütze (1996) ; Takunaga et al. (1998) ; Lin (1998) ). This paper investigates the use of a cost-effective way to el... | 0 |
Winograd Schemas (henceforth "WS"), introduced by Levesque et al. (2012) , are pairs of short reading comprehension problems that usually amount to finding the antecedent of an anaphoric expression. They constitute a theoretically motivated benchmark for Natural Language Understanding (NLU) that is also one of the most... | 0 |
Voice control of devices we use in our daily lives is still perceived as a luxury, since often cheaper and more straightforward alternatives are available, such as pushing a button or using remote controls. But what if pushing buttons is not trivial? Physically impaired people with restricted (upper) limb motor control... | 0 |
Information Extraction (IE), a fundamental task in natural language processing, aims to extract structured knowledge from unstructured texts. It usually contains the process that extracts text spans (such as words or phrases) from plain text, e.g., NER. Span extraction is usually formulated into the se- Figure 1 : Illu... | 0 |
The emergence of Neural Machine Translation (NMT) was sparked by the use of Recurrent Neural Networks (RNN) for machine translation. The RNN encoder in this approach is responsible for encoding the source language phrase into a fixedlength vector. This vector is then decoded into the target language (Cho et. al., 2014)... | 0 |
Discourse connectives should preserve their sense during translation, as they are often ambiguous and may convey more than one sense depending on the inter-sentential relation (causality, concession, contrast or temporal). For instance, since in English can express temporal simultaneity, but also a causal sense.In this... | 0 |
The goal of Multi-Document Summarization (MDS) is to automatically produce a succinct summary, preserving the most important information of a set of documents describing a topic 1 (Luhn, 1958; Edmundson, 1969; Goldstein et al., 2000; Erkan and Radev, 2004b; Wan et al., 2007; Nenkova and McKeown, 2012) . Considering the... | 0 |
Neural language models (LMs) (Devlin et al., 2019; Radford et al., 2019; Liu et al., 2019) are today a key enabler in NLP. They have contributed to a general uplift in downstream performance across many applications, even sometimes rivaling human judgement (Wang et al., 2018 (Wang et al., , 2019 , while also bringing a... | 0 |
Each Machine processing of Natural (Human) Languages has a long tradition, benefiting from decades of manual and semi-automatic analysis by linguists, sociologists, psychologists and computer scientists among others. Development of a full-fledged bilingual Machine Translation (MT) system for any two natural languages w... | 0 |
Document summarization has been the focus of many researchers for the last decade, due to the increase in on-line information and the need to find the most important information in a (set of) document(s). One of the biggest challenges in text summarization research is how to evaluate the quality of a summary or the per... | 0 |
Neural networks have become the defacto approach for various natural language processing tasks, in- 1 Following the prior work on adversarial learning, worstcase adversarial attacks mean adversarial examples generated by attacking specific models.2 Our code and dataset is available at https://github.com/ygan/Spider-Syn... | 0 |
Being able to recognize aspects of discourse structure has recently been shown to be relevant for tasks as diverse as machine translation, questionanswering, text summarization, and sentiment analysis. For many of these applications, a 'shallow' approach as embodied in the PDTB can be effective. It is shallow in the se... | 0 |
A great amount of progress has been made in the area of automated fact-checking. This includes more accurate machine learning models for veracity prediction and datasets of both naturally occurring (Wang, 2017; Augenstein et al., 2019; Hanselowski et al., 2019) and human-crafted (Thorne et al., 2018) fact-checking clai... | 0 |
Uncovering the syntactic structure of texts is a necessary step towards extracting their meaning. In order to obtain an accurate parse for an unseen text, we need to assign Part-of-Speech (PoS) tags to a string of words. This paper covers one aspect of our work of PoS tagging with Dynamic Bayesian Networks (DBNs), whic... | 0 |
In recent years natural language processing has experienced rapid development. In particular, application of deep learning to NLP (Collobert et al., 2011) , the introduction of pre-trained context-independent word embeddings such as word2vec (Mikolov et al., 2013a; Mikolov et al., 2013b) , GloVe (Pennington et al., 201... | 0 |
Few-shot text generation is an important research topic since obtaining large-scale training data for each individual downstream task is prohibitively expensive. Recently, pretraining large neural networks with a language modeling objective has led to significant improvements across different fewshot text generation ta... | 0 |
Noun phrase (NP) coreference resolution is one of the fundamental tasks of the field of Natural Language Processing (NLP). Recently, the creation of the OntoNotes corpus (Pradhan et al., 2007) has provided researchers with a large standard data collection with which to create and empirically compare coreference resolut... | 0 |
Biomedical event extraction is a task that identifies a set of actions among proteins or genes that are associated with biological processes from natural language texts (Kim et al., 2009 (Kim et al., , 2011 . Development of biomedical event extraction tools enables many downstream applications, such as domain-specific ... | 0 |
Historical text presents numerous challenges for contemporary natural language processing techniques. In particular, the absence of consistent orthographic conventions in historical text presents difficulties for any system requiring reference to a fixed lexicon accessed by orthographic form, such as document indexing ... | 0 |
Named entities play a central role in conveying important domain specific information in text, and good named entity recognizers are often required in building practical information extraction systems. Previous studies have shown that automatic named entity recognition can be performed with a reasonable level of accura... | 0 |
Automatic Essay Scoring(AES) is one of the most important Natural Language Processing (NLP) applications in the field of education (Page, 1966; Ke and Ng, 2019) , and has been widely used in standardized language tests (Burstein and Chodorow, 1999; Attali and Burstein, 2006) . However, existing works mainly focus on th... | 0 |
Currently, most extractive models treat summarization as a sequence labeling task. They score and select sentences one by one (Zhong et al., 2020) .These models (called sentence-level extractors) do not consider summary as a whole but a combination of independent sentences. This may cause incoherent and redundant probl... | 0 |
What words might a menu writer use to justify the high price of a steak? How does describing an item as chargrilled vs. charbroiled affect its price? When a customer writes an unfavorable review of a restaurant, how is her word choice affected by the restaurant's prices? In this paper, we explore questions like these t... | 0 |
Persuasive discourses are common in social media. Recently, the automatic identification of such persuasive discourse is receiving attention in the field of computational linguistics (Habernal and Gurevych, 2016b; Tan et al., 2016; Habernal and Gurevych, 2016a; Persing and Ng, 2017; Hidey and McKeown, 2018; Ji et al., ... | 0 |
Collecting data from the web for commercial and research purposes has become a popular task, used for a wide variety of purposes in text and speech processing. However, to date, most of this data collection has been done for English and other High Resource Languages (HRLs). These languages are characterized by having e... | 0 |
Word alignments are essential for statistical machine translation (MT), especially in low-resource settings where neural MT systems often do not compete with phrase-based and syntax-based MT (Koehn and Knowles, 2017) . The most widely used word alignment method (Brown et al., 1993) works by estimating the parameters of... | 0 |
Event extraction (EE) aims to extract events, each of which consists of a trigger and several participants (arguments) with their specific roles, from a given passage. For example, in Figure 1 , a Justice:Execute event is triggered by the word "execution" and this event contains three argument roles, including an Agent... | 0 |
Traditional search models over scholarly communication are now changing toward Knowledge Graph (KG) models operating on structured fine-grained scholarly content offering enhanced contextual search results. Several initiatives exist to this end: Google Scholar, Web of Science (Birkle et al., 2020) , Microsoft Academic ... | 0 |
Cross lingual information access (CLIA) systems enable users to access the rich multilingual content that is created on the web daily. Such systems are vital to bridge the gap between information available and languages known to the user. Considerable amount of research has been done on building such systems but most o... | 0 |
A web-based automated reading strategy trainer called iSTART (Interactive Strategy Trainer for Active Reading and Thinking) adaptively assigns individual students to appropriate reading training programs. It follows the SERT (Self-Explanation Reading Training) methodology developed by McNamara (in press ) as a way to i... | 0 |
Allowing patients access to their own electronic health records (EHRs) can enhance medical understanding and provide clinical relevant benefits (Wiljer et al., 2006) , including increased medication adherence (Delbanco et al., 2012) . However, EHR notes present unique challenges to the average patients. Since these not... | 0 |
Language is a rich repository of information about our practices, constituting raw material for research in Human and Social Sciences. In close connection with Computational Linguistics, Humanities and Social Sciences, the growing field of the Digital Humanities has at its disposal tools and resources that offer new wa... | 0 |
Sentiment analysis refers to a series of methods, techniques, and tools aimed at extracting the intended sentiment from a written opinion. Traditional sentiment analysis techniques have relied on using supervised term weighting methods including terms' distribution of classes, word-level polarity scoring and using SVMs... | 0 |
Words in two languages that are orthographically and/or phonetically similar are often perceived as mutual translations, which could be wrong in some contexts. Such words are known as cognates 1 when they are mutual translations in all contexts, partial cognates when they are mutual translations in some contexts but no... | 0 |
Solving commonsense QA tasks requires filling gaps with external knowledge. For instance, given the multiple-choice question in Figure 1 , a system needs to know that fungus grows in moist environments, such as caves, and that a cave is a type of geological feature. Such commonsense knowledge is obvious for humans but ... | 0 |
Word embeddings have been widely used as features in NLP tasks like parsing and textual entailment. One key aspect that has been investigated is their capacity to encode hypernymy; this semantic relation denotes a taxonomical order of objects in the world; for example, a dog is a canine which is a vertebrate. To test t... | 0 |
Reading and understanding text is a task that requires the ability to disambiguate at several levels, abstracting away details and using background knowledge in a variety of ways. One of the difficulties that humans resolve instantaneously and unconsciously is that of reading names. Most names of people, locations, org... | 0 |
The selection of relevant feature sets is crucial to the performance of dependency parsers and this process is still in large part manual. More-over, feature sets are specific to the languages being analyzed and a set optimal for, say, English can yield poor results in Chinese. With dependency parsers being applied tod... | 0 |
In many situations, we use subjective expressions that convey emotions, feelings and evaluations about someone or something. It is essential to be able to understand such expressions, and in particular, to be able to use them in language generation tasks. One kind of text that involves subjective expressions is a revie... | 0 |
SMT from a morphologically poor language like English into a language with richer morphology continues to be a problem, in particular when training data is sparse and/or the SMT system has insufficient modeling capabilities for morphological variation in the target language. Most previous approaches to this problem hav... | 0 |
For graph based projective dependency parsing, dynamic programming (DP) is popular for decoding due to its efficiency when handling local features. It performs cubic time parsing for arc-factored models (Eisner, 1996; McDonald et al., 2005a) and biquadratic time for higher order models with richer sibling and grandchil... | 0 |
Categorial Grammars, in their various incarnations, posit a functional view on parsing: words are assigned simple or complex categories (or: types); their composition is modeled in terms of functor-argument relationships. Complex categories wear their combinatorics on their sleeve, which means that most of the phrasal ... | 0 |
In the past decade, the semantics of evaluative language has received renewed attention in both formal and computational linguistics (Martin and White, 2005; Potts, 2005; Pang and Lee, 2008; Jackendoff, 2007) . This work has focused on evaluativity at either the lexical level or the phrasal/event level stance, without ... | 0 |
Water crisis is one of the pressing current environmental challenges. More than a billion people do not have access to clean drinking water, and every year nearly two million children die from water borne diseases (Watkins, 2006) . One-third of the world's most extensive groundwater systems are under severe stress (Ric... | 0 |
Sentiments have been widely studied as they play an important role in human intelligence, rational decision making, social interaction, perception, memory, learning and creativity (Pang and Lee, 2008; Strapparava and Mihalcea, 2008; Maas et al., 2011; Li et al., 2015) . The ability to discern and understand human senti... | 0 |
Cross-lingual word embeddings (CLWEs) are a mainstay of modern cross-lingual NLP (Ruder et al., 2019b) . CLWE models induce a shared cross-lingual vector space in which words with similar meanings obtain similar vectors regardless of their language. Their usefulness has been attested in tasks such as bilingual lexicon ... | 0 |
Direct perception of our environment is just one of the ways we can acquire knowledge of the world. Another, more distinctly human approach, is through the comprehension of linguistic descriptions of another person's perceptions and beliefs.Since computers have limited means of human-like perception, the latter approac... | 0 |
Named Entity Recognition (NER) is concerned with the identification of named entities, such as persons, locations, and organizations, in unstructured text. NER plays an important role in many downstream tasks, including knowledge base construction (Riedel et al., 2013) , information retrieval (Chen et al., 2015) , and ... | 0 |
Les applications de traitement automatique des langues (TAL) ont de plus en plus besoin d'informations lexicales. La disponibilité de telles ressources et leur utilisabilité dans les applications de TAL restent pourtant relatives.Deux approches sont possibles pour la constitution de telles ressources : la construction ... | 0 |
Dialect can be defined as the language characteristics of a specific community (Etman and Beex, 2015) . For all their daily communications, Arabic speakers use their local dialect. Dialects are commonly known as spoken or colloquial Arabic, acquired naturally as their mother tongue.Being able to identify the dialect of... | 0 |
Neural machine translation models have achieved great success in recent years Bahdanau et al., 2015; Gehring et al., 2017; Vaswani et al., 2017) . Despite their efficiency and superb performance, NMT models are prone to over-fitting that universal regularization techniques such as dropout (Hinton et al., 2012) and labe... | 0 |
Making manual annotations is a common task when a high-quality language resource is created. The more complex the annotation task, the more time consuming it is for an annotator, an expert in a linguistic field captured by the resource. Consequently, the cost of creating such resource can be high. The simplest approach... | 0 |
This paper describes a system that addresses the problem of assessing semantic similarity between two different-sized texts. The system has been applied to SemEval-2014 Task 3, Cross-Level Semantic Similarity (Jurgens et al, 2014) . The application is limited to a single comparison type, that is, paragraph to sentence.... | 0 |
Since the introduction of pretrained word embeddings (Mikolov et al., 2013b; Pennington et al., 2014) , unsupervised representation learning has become an essential part of Natural Language Processing (NLP). The idea of exploiting unlabeled corpuses to improve performance on downstream NLP tasks has been excelled in re... | 0 |
In this work, we present evaluation metrics for summary content which make use of little or no human involvement. Evaluation methods such as manual pyramid scores (Nenkova, Passonneau, and McKeown 2007) and automatic ROUGE scores (Lin and Hovy 2003) rely on multiple human summaries as a gold standard (model) against wh... | 0 |
The concept of coherence is based on cohesive semantic relations connecting elements of a text. Cohesive relations are expressed through grammar and the vocabulary of a language. The former is referred to as grammatical coherence, the latter as lexical coherence (Halliday and Hasan, 1976) . Grammatical coherence encomp... | 0 |
Technologies for handheld devices with open platforms have made rapid progresses. Recently open-platforms Android is getting momentum. Mobile devices with microphone and speaker, video camera, touch screen, GPS, etc, are served as sensors for experiencing with augmented reality in human life. Speech synthesis may becom... | 0 |
Statistical Machine Translation defines the task of translating a source language sentence where the search component is commonly referred to as the decoding step (Wang and Waibel, 1998) . Within the generative model, the Bayes reformulation is used to estimate , at the cost of deviating from the Bayesian framework. Re... | 0 |
In remote Aboriginal communities in Australia, many efforts are made to document traditional knowledge including rock art, medicinal plants, and food practices. While it may be relatively straightforward to capture spoken content, transcription is time-consuming and has been described as a bottleneck (Brinckmann, 2009)... | 0 |
Intent classification and slot labeling are two fundamental components in task-oriented dialog systems, producing a formal meaning representation for an utterance that the system can act upon to fulfill the user's request. As shown in Figure 1 , it is typically modeled by classifying the utterance into a set of support... | 0 |
Neural Machine Translation (NMT) has made significant progress in various machine translation tasks (Kalchbrenner and Blunsom, 2013; Sutskever et al., 2014; Bahdanau et al., 2014; Luong et al., 2015; Wu et al., 2016) . The success of NMT heavily relies on a huge amount of annotated parallel sentences as training data, ... | 0 |
Parsing has often been considered to be crucial for natural language processing, thus, efficient and wide coverage parsing has been extensively pursued in natural language literature. This study aims at robust processing within the Head-driven Phrase Structure Grammar (HPSG) to extend the coverage of manually-developed... | 0 |
Keyword extraction is the process of identifying a short list of words or noun phrases that capture the most important ideas or topics covered in a document. Keyword extraction has been used in a variety of natural language processing applications, such as informat ion retrieval systems, digital library searching, web ... | 0 |
Every day millions of people search for images on the web, both professionally and for personal amusement. The majority of image searches are aimed at finding a particular named entity, such as Justin Bieber or supernova, and a typical image retrieval system is well-suited to this type of information need because it re... | 0 |
In our research, to help people quickly having an overview of a topic or an event, we automatically collect articles from online newspapers related to that topic or event, and summarize them. We should be able to make a summarized document from those articles by extracting important sentences. However, there is a lot o... | 0 |
Currently, bi-and multilingual wordnets are most commonly inter-linked on the synset level, (e.g., Bond and Foster, 2013) . Synsets can be composed of one or more lexical units (lemma-PoS-synset triples, also called senses; henceforth, LUs), so such inter-wordnet links may be of three types: 1-to-1 sense link (between ... | 0 |
Named Entity Recognition (NER) is the task of detecting entity spans and then classifying them into predefined categories, such as person, location and organization. Due to the capability of extracting entity information and benefiting many NLP applications (e.g., relation extraction (Lin et al., 2017) , question answe... | 0 |
Recommendation dialog systems have been developed for a number of tasks ranging from product search to restaurant recommendation (Chai et al., 2002; Thompson et al., 2004; Bridge et al., 2005; Young et al., 2010) . These systems learn user requirements through spoken or text-based dialog, asking questions about particu... | 0 |
Morphological analysis and morphological generation are two tasks shared by many applications in the field of NLP. Closely connected to these tasks, one of the main issues at hand when designing such applications is how to organize and store in the lexicon the morphological information needed to analyze and generate wo... | 0 |
Algorithms for tactical generation are becoming an increasingly important subject of research in computational linguistics (Shieber, 1988; Shieber et al., 1989; Calder et al., 1989) . In this paper, we will discuss generation algorithms within the Lambek Theorem Proving (LTP) framework (Moortgat, 1988; Lambek, 1958; va... | 0 |
Even if not perfect, machine translation (MT) is now getting reliable enough to support and speedup human translation. Thanks to this progress, the work of professional translators is gradually shifting from full translation from scratch to MT post-editing. Advanced computer-assisted translation (CAT) tools 1 provide a... | 0 |
Turkish Discourse Bank (TDB) is the first discourse-annotated corpus of Turkish, which follows the principles of Penn Discourse Tree Bank (PDTB) (Prasad et al., 2008) and includes annotations for discourse connectives, their arguments, modifiers and supplements of the arguments. The TDB is built on a ~ 400,000-word sub... | 0 |
In this paper, we describe our submission to the MultiIndicMT shared task at the 8th Workshop on Asian Translation 1 (WAT 2021) (Nakazawa et al., 2021) . The objective of this shared task is to build Machine Translation (MT) models between 10 Indic languages (Bengali, Gujarati, Hindi, Kannada, Malayalam, Marathi, Odia,... | 0 |
Most approaches to modeling conversation are based on a strong notion of cooperation between the dialogue participants (DPs). Traditional models using intentions (Cohen and Levesque, 1991) , dialogue games (Power, 1979) , shared plans (Grosz and Sidner, 1990) or collaborative problem-solving (Blaylock and Allen, 2005) ... | 0 |
Biblical Hebrew is the archaic form of Hebrew in which the Hebrew Bible is primarily written. Its syntax and vocabulary differ from later Rabbinic Hebrew and Modern Hebrew. Hebrew is a highly inflected language, and the key to understanding any Hebrew word is to identify and understand its root. For example, the first ... | 0 |
Dialog policy for multi-turn dialogue decides the next best action to take on the environment so as to complete the conversation based on various success criteria. Reinforcement learning can help to learn such a policy where the environment can be users (human or model) and the policy takes action on the environment fr... | 0 |
METU-Sabancı Treebank is a dependency treebank of about 5600 modern day Turkish sentences annotated with surface dependency graphs (Atalay et al., 2003; . The words in the treebank are annotated with their morphological structure.However, only the tag information is used in the annotations. These tags are combined to c... | 0 |
Models of human sentence processing difficulty can be divided into two kinds, expectation-based and memory-based. Expectation-based models predict the processing difficulty of a word from the word's surprisal given previous material in the sentence (Hale, 2001; Levy, 2008a) . These models have good coverage: they can a... | 0 |
Over the years, there have been several multimodal systems that allow input and/or output to be conveyed over multiple channels such as speech, graphics, and gesture, for example, put that there (Bolt, 1980) , CUBRICON (Neal and Shapiro, 1991) , QuickSet (Cohen et al., 1998) , SmartKom (Wahlster, 2002) , Match . Multim... | 0 |
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