Linguistic Features

The development of natural language pro- ccssing (NLP) systems that perform ma- chine translation (MT) and information re- trieval (IR) has highlighted the need for the automatic recognition of proper …...

This paper describes a robust linear classifica- tion system for Named Entity Recognition. A similar system has been applied to the CoNLL text chunking shared task with state of the …...

Temporal relation resolution involves extraction of temporal information explicitly or implicitly embedded in a language. This information is of- ten inferred from a variety of interactive gram- matical and lexical …...

Temporal reference is an issue of determining how events relate to one another. Determining temporal relations relies on the combination of the information, which is explicit or implicit in a …...

We examine the utility of multiple types of turn-level and contextual linguistic features for automatically predicting student emotions in human-human spoken tutoring dialogues. We first annotate student turns in our …...

. In this paper we investigate the possibility of evaluating MT quality and fluency at the sentence level in the absence of reference translations. We measure the correlation between automatically-generated …...

. The current work applies Conditional Random Fields to the problem of temporal reference mapping from Chinese text to English text. The learning algorithm utilizes a moderate number of linguistic …...

The driving vision for our work is to provide intelligent, automated assistance to users in understanding the status of their email conversations. Our approach is to create tools that enable …...

The immense prosodic variation of natural con- versational speech makes it challenging to pre- dict which words are prosodically prominent in this genre. In this paper, we examine a new …...

We explore the problem of resolving the second person English pronoun you in multi-party dialogue, using a combination of linguistic and visual features. First, we distinguish generic and referential uses, …...

A machine translated sentence is seldom completely correct. Confidence measures are designed to detect incorrect words, phrases or sentences, or to provide an esti- mation of the probability of correctness. …...

Automatic error detection is desired in the post-processing to improve machine translation quality. The previous work is largely based on confidence estimation us- ing system-based features, such as word posterior …...

A range of Natural Language Process- ing tasks involve making judgments about the semantic relatedness of a pair of sen- tences, such as Recognizing Textual En- tailment (RTE) and answer …...

AbstractIt is recognized that many evaluation metrics of machine translation in use that focus on surface word level suffer from their lack of tolerance of linguistic variance, and the incorporation …...

Machine learning approaches for Information Extraction use different types of features to acquire semantically related terms from free text. These features may contain several kinds of linguistic knowledge: from orthographic …...

Arabic handwriting recognition (HR) is a challenging problem due to Arabic’s con- nected letter forms, consonantal diacritics and rich morphology. In this paper we isolate the task of identification of …...

AbstractIn this paper, we present corpus-based procedures to semi-automatically discover features relevant for the study of recent language change in scientific registers. First, linguistic features potentially adherent to recent language …...

This paper describes a study on the contribu- tion of linguistically-informed features to the task of quality estimation for machine trans- lation at sentence level. A standard regression algorithm is …...

Scientific publications contain many references to method terminologies used during scientific experiments. New terms are constantly created within the research community, especially in the biomedical domain where thousands of papers …...

In this article, we present a novel approach towards the detection and modeling of complex social phenomena in multi-party discourse, including leadership, influence, pursuit of power and group cohesion. We …...

We consider the task of automatically es- timating the value of human actions. We cast the problem as a supervised learning- to-rank problem between pairs of action descriptions. We present …...

AbstractThere are several MT metrics used to evaluate translation into Spanish, although most of them use partial or little linguistic information. In this paper we present the multilingual capability of …...

In this paper, we look at three different meth- ods of extracting the argumentative structure from a piece of natural language text. These methods cover linguistic features, changes in the …...

Sentiment Analysis of tweets is a complex task, because these short messages employ unconventional language to increase the ex- pressiveness. This task becomes even more difficult when people use figurative …...

AbstractWe propose a hierarchical clustering approach designed to group linguistic features for supervised machine learning that is inspired by variationist linguistics. The method makes it possible to abstract away from …...

AbstractThis paper presents some preliminary results of the OPLON project. It aimed at identifying early linguistic symptoms of cognitive decline in the elderly. This pilot study was conducted on a …...

Given the limited success of medication in re- versing the effects of Alzheimer’s and other dementias, a lot of the neuroscience research has been focused on early detection, in order …...

Metaphor is pervasive in our communication, which makes it an important problem for nat- ural language processing (NLP). Numerous approaches to metaphor processing have thus been proposed, all of which …...

This paper describes our systems submitted to the Sentence-level and Text-level Aspect- Based Sentiment Analysis (ABSA) task (i.e., Task 5) in SemEval-2016. The task involves two phases, namely, Aspect Detection …...

This paper describes our system submissions to task 7 in SemEval 2016, i.e., Determining Sentiment Intensity. We participated the first two subtasks in English, which are to predict the sentiment …...

AbstractThis paper presents a data-driven co-reference resolution system for German that has been adapted from IMS HotCoref, a co-reference resolver for English. It describes the difficulties when resolving co-reference in …...

This paper presents our contribution to the Se- mEval 2016 task 5: Aspect-Based Sentiment Analysis. We have addressed Subtask 1 for the restaurant domain, in English and French, which implies …...

AbstractThere have been many attempts at automatically recognising author personality traits from text, typically incorporating linguistic features with conventional machine learning models, e.g. linear regression or Support Vector Machines. In …...

AbstractIn this paper, we present a novel approach to infer significance of various textual edits to documents. An author may make several edits to a document; each edit varies in …...

AbstractThis paper describes our systems submitted to the Fine-Grained Sentiment Analysis on Financial Microblogs and News task (i.e., Task 5) in SemEval-2017. This task includes two subtasks in microblogs and …...

AbstractNeural networks with attention have proven effective for many natural language processing tasks. In this paper, we develop attention mechanisms for uncertainty detection. In particular, we generalize standardly used attention …...

Under the issue of gender and Natural Language Processing (NLP), most papers aim at gender- norm language that spoken by biologically males and females with opposite-sex desires. However, from the …...

AbstractDebate and deliberation play essential roles in politics and government, but most models presume that debates are won mainly via superior style or agenda control. Ideally, however, debates would be …...

We introduce Arabic Data Science Toolkit (ADST), a framework for Arabic language feature extraction, designed for data scientists that may not be familiar with Arabic or natural language processing. The …...

AbstractWe introduce a scalable Bayesian preference learning method for identifying convincing arguments in the absence of gold-standard ratings or rankings. In contrast to previous work, we avoid the need for …...

AbstractWe explore deception detection in interview dialogues. We analyze a set of linguistic features in both truthful and deceptive responses to interview questions. We also study the perception of deception, …...

AbstractSluicing resolution is the task of identifying the antecedent to a question ellipsis. Antecedents are often sentential constituents, and previous work has therefore relied on syntactic parsing, together with complex …...

AbstractThe overall machine translation quality available for professional translators working with the Spanish–Basque pair is rather poor, which is a deterrent for its adoption. This work investigates the plausibility of …...

AbstractThis work lays the foundation for automated assessments of narrative quality in student writing. We first manually score essays for narrative-relevant traits and sub-traits, and measure inter-annotator agreement. We then …...

AbstractExisting argumentation datasets have succeeded in allowing researchers to develop computational methods for analyzing the content, structure and linguistic features of argumentative text. They have been much less successful in …...

AbstractWhen a speaker, Mary, asks “Do you know that Florence is packed with visitors?”, we take her to believe that Florence is packed with visitors, but not if she asks …...

AbstractOnline debates allow people to express their persuasive abilities and provide exciting opportunities for understanding persuasion. Prior studies have focused on studying persuasion in debate content, but without accounting for …...

AbstractWith the growth in the usage of social media, it has become increasingly common for people to hide behind a mask and abuse others. We have attempted to detect such …...

AbstractTextual content is the most significant as well as substantially the big part of CQA (Community Question Answering) forums. Users gain reputation for contributing such content. Although linguistic quality is …...

AbstractIndependently of the medial representation (written/spoken), language can exhibit characteristics of conceptual orality or literacy, which mainly manifest themselves on the lexical or syntactic level. In this paper we aim …...

AbstractWe present a neural network approach to estimate the communication style of spoken interaction, namely the stylistic variations elaborateness and directness, and investigate which type of input features to the …...

AbstractThe recent dominance of machine learning-based natural language processing methods has fostered the culture of overemphasizing model accuracies rather than studying the reasons behind their errors. Interpretability, however, is a …...

AbstractIn a context of offensive content mediation on social media now regulated by European laws, it is important not only to be able to automatically detect sexist content but also …...

AbstractSeveral quality dimensions of natural language arguments have been investigated. Some are likely to be reflected in linguistic features (e.g., an argument’s arrangement), whereas others depend on context (e.g., relevance) …...

AbstractThe objective of this research is to estimate multidimensional subjective ratings of the reading performance of young readers from signal-based objective measures. We here combine linguistic features (number of correct …...

AbstractDialogue act classification becomes a complex task when dealing with fine-grain labels. Many applications require such level of labelling, typically automatic dialogue systems. We present in this paper a 2-level …...

AbstractSentence complexity assessment is a relatively new task in Natural Language Processing. One of its aims is to highlight in a text which sentences are more complex to support the …...

It is well known that human is not good at de- ception detection because of a natural inclina- tion of truth-bias. However, during a conversa- tion, when an interlocutor (interrogator) …...

AbstractOne of the mechanisms through which disinformation is spreading online, in particular through social media, is by employing propaganda techniques. These include specific rhetorical and psychological strategies, ranging from leveraging …...

AbstractWith the increasing popularity of learning Chinese as a second language (L2) the development of an automatic essay scoring (AES) method specially for Chinese L2 essays has become animportant task. …...

English research articles (RAs) are an essential genre in academia, so the attempts to employ NLP to assist the development of academic writing ability have received considerable attention in the …...

AbstractA common factor in bias measurement methods is the use of hand-curated seed lexicons, but there remains little guidance for their selection. We gather seeds used in prior work, documenting …...

AbstractThis paper presents the system we submitted to the first Lexical Complexity Prediction (LCP) Shared Task 2021. The Shared Task provides participants with a new English dataset that includes context …...

Studies based on linguistic theories have reported that internet celebrities em- ploy various persuasion strategies in their speeches. Since persuasion is closely re- lated to pragmatics which involves peo- ple’s …...

AbstractWe examine the task of detecting implicitly abusive comparisons (e.g. “Your hair looks like you have been electrocuted”). Implicitly abusive comparisons are abusive comparisons in which abusive words (e.g. “dumbass” …...

AbstractDeep learning models for automatic readability assessment generally discard linguistic features traditionally used in machine learning models for the task. We propose to incorporate linguistic features into neural network models …...

In this paper, we describe the results of our research aimed at detecting depression in Japanese sentences. In the United States and elsewhere, machine learning approaches to detect depression from …...

AbstractBlack-box probing models can reliably extract linguistic features like tense, number, and syntactic role from pretrained word representations. However, the manner in which these features are encoded in representations remains …...

AbstractEver-expanding evaluative texts on online forums have become an important source of sentiment analysis. This paper proposes an aspect-based annotated dataset consisting of telecom reviews on social media. We introduce …...

AbstractRecent pre-trained language models (PLMs) achieved great success on many natural language processing tasks through learning linguistic features and contextualized sentence representation. Since attributes captured in stacked layers of PLMs …...

AbstractDifficulties with social aspects of language are among the hallmarks of autism spectrum disorder (ASD). These communication differences are thought to contribute to the challenges that adults with ASD experience …...

AbstractIn this article, we seek to automatically identify Hungarian patients suffering from mild cognitive impairment (MCI) or mild Alzheimer disease (mAD) based on their speech transcripts, focusing only on linguistic …...

AbstractIn the field of Natural Language Processing (NLP), extracting method entities from biomedical text has been a challenging task. Scientific research papers commonly consist of complex keywords and domain-specific terminologies, …...

AbstractIn recent years, neural models have often outperformed rule-based and classic Machine Learning approaches in NLG. These classic approaches are now often disregarded, for example when new neural models are …...

AbstractFeature Engineering consists in the application of domain knowledge to select and transform relevant features to build efficient machine learning models. In the Natural Language Processing field, the state of …...