Characteristics of email threads concerning reference resolution are first discussed, and then the creation of the corpus and annotation steps are explained. Improving automatic correction of misspellings, for writers who are native speakers of English, and especially for English Language Learners (ELLs), and for EFL students. We expect that this finding also holds for the other languages, http://www.lrec-conf.org/proceedings/lrec2020/pdf/2020.lrec-1.43.pdf, Immersive Language Exploration with Object Recognition and Augmented Reality, Benny Platte, Anett Platte, Christian Roschke, Rico Thomanek, Thony Rolletschke, Frank Zimmer and Marc Ritter. This paper addresses the difficult problems of constructing a corpus of ISAs, taking inspiration from relevant work in using corpora for reasoning tasks. http://www.lrec-conf.org/proceedings/lrec2020/pdf/2020.lrec-1.17.pdf, ZuCo 2.0: A Dataset of Physiological Recordings During Natural Reading and Annotation, Nora Hollenstein, Marius Troendle, Ce Zhang and Nicolas Langer. We evaluate our model on data from a medical domain and demonstrate that it rivals the performance of a model trained and tuned on in-domain data. Following previous work, we model the neighborhood effect as the average distance to neighbors in feature space for three feature sets: slots, character ngrams and skipgrams. Identifying and resolving such omitted arguments is crucial to machine translation, information extraction and other NLP tasks, but depends heavily on semantic coherence and lexical relationships. http://www.lrec-conf.org/proceedings/lrec2020/pdf/2020.lrec-1.87.pdf, Intent Recognition in Doctor-Patient Interviews, Robin Rojowiec, Benjamin Roth and Maximilian Fink. The paper describes the findings from neuroscience, phonetics and the science of evolution leading to the AC-hypotheses. The initial analysis is performed at the individual level and later, we combine the different modalities to observe their impact on perceived level of cohesion. Then, we evaluate several retrieval-based and generative models to provide basic benchmark performance on the JDDC corpus. Learning to interview patients to find out their disease is an essential part of the training of medical students. http://www.lrec-conf.org/proceedings/lrec2020/pdf/2020.lrec-1.90.pdf, Predicting Ratings of Real Dialogue Participants from Artificial Data and Ratings of Human Dialogue Observers, Kallirroi Georgila, Carla Gordon, Volodymyr Yanov and David Traum. The dataset is annotated with orthographic transcriptions of utterances and information on: (a) gaze behaviours, (b) when a participant touched an object, (c) when an object was moved, (d) when a participant looked at the location s/he would next move the object to, (e) when the participant’s gaze was stable on an area. of relating our experiences to other subjects and, monly used to help us understand the world in a, the unknown using the known, explains the com-, plex using the simple, and helps us to emphasize, the relevant aspects of meaning resulting in ef, There is a large body of work in the litera-, ture that discusses how metaphor has been used in. http://www.lrec-conf.org/proceedings/lrec2020/pdf/2020.lrec-1.67.pdf, Estimating User Communication Styles for Spoken Dialogue Systems, Juliana Miehle, Isabel Feustel, Julia Hornauer, Wolfgang Minker and Stefan Ultes. The proposed work is an attempt to exploit one of these new milestones to handle multi-turn conversations. The paper examines this effect with respect to word embeddings. http://www.lrec-conf.org/proceedings/lrec2020/pdf/2020.lrec-1.15.pdf, Modelling Narrative Elements in a Short Story: A Study on Annotation Schemes and Guidelines, Elena Mikhalkova, Timofei Protasov, Polina Sokolova, Anastasiia Bashmakova and Anastasiia Drozdova. They also began using the common language in worship services. However, most of the textual and multi-modal conversational emotion corpora contain only emotion labels but not dialogue acts. Our contribution consists of a sequence of experiments using BERT, starting with a baseline, strengthening it by spell-correcting the TOEFL corpus , followed by a multi-task learning setting , where one of the tasks is the token-level metaphor classification as per the shared task, while the other is meant to provide additional training that we hypothesized to be relevant to the main task. The Room of Ancient Keys. These transcriptions are based on audio recordings of exercise sessions within the university and only the doctor's utterances could be transcribed. Although no significant differences are found between implicit and explicit strategies, proactivity significantly influences the user experience compared to reactive system behaviour. Secondly, follow-up work (Lee et al., 2019) has augmented the original dataset with user dialogue acts. The first results are encouraging. http://www.lrec-conf.org/proceedings/lrec2020/pdf/2020.lrec-1.31.pdf. Not in Library. This work proposes a linguistically enhanced model for metaphor detection extending one published work (WAN et. We explain this result with the loss of contextual information, reduction of the relative occurrence of rare words and the lack of pronouns to be replaced. Based on the lack of dialogue corpora in French for medical education, we propose an annotatedcorpus of dialogues including medical consultation interactions between doctor and patient. By testing on three public datasets, we find that our models achieve state-of-the-art performance in end-to-end metaphor identification. We then present an international network called the European Network for Combining Language Learning with Crowdsourcing Techniques (enetCollect) that provides the context to accelerate the implementation of this generic approach. Elena Konstantinovna Mikhailovskaya (russe : Елена Константиновна Михайловская ; 21 novembre 1949 à Moscou - 4 février 1995 à Moscou) a été la première championne du monde du jeu de dames internationales.Elle a remporté ce titre à cinq reprises à la suite (1973-1977). For the yes/no response classifier, the macro-average of the average precisions (APs) over all of our four categories (Yes/No/Unknown/Other) was 82.6% (96.3% for "yes" responses and 91.8% for "no" responses), while for the entailment recognizer it was 89.9%. We ran experiments with the Balanced Bagging Classifier (BAGC), Condiontal Random Field (CRF), and several Long Short Term Memory (LSTM) networks, and found that all of them improved compared to the baseline (e.g., without the data augmentation pipeline). Nonetheless, how to provide suggestions is still an open question. We make the pilot version of the Russian ReLCo publicly available. Therefore, we aim to provide proactive PA suggestions to car drivers via speech. Given the limited size of existing idiom corpora, we aim to enable progress in automatic idiom processing and linguistic analysis by creating the largest-to-date corpus of idioms for English. In this research, responsive utterances are classified into five levels based on the effect of utterances and literature on attentive listening. Finally, we perform the tasks of detection and resolution of noun ellipsis with different classifiers trained on our corpus and report baseline results. The data was annotated, the metaphor annotations marked as such by the, 60 essays for testing, as provided by the shared, scriptive characteristics of the data: the number of, texts, sentences, tokens, and class distribution in-, trained on a large quantity of texts, and obtained, state-of-the-art performance on many NLP bench-, ken classification task, that is, after obtaining the, contextualized embeddings of a sentence, we ap-, ply a linear layer followed by softmax on each, token to predict whether it is metaphorical or, tions for the VUA corpus are the same as the ones, folds information from the shared task organiz-, anced class distribution in our data (see T. the positive class is up-weighted by a factor of 3. We use this corpus to estimate the elaborateness and the directness of each utterance. We applied this method to the partially subjective task of speech classification into the following four attitudes: agreement, disagreement, stalling, and question. Together with other values obtained from monolingual and parallel corpora, we can indicate which entries need to be adjusted to obtain values that are even more in line with this gold standard. It also covers various dialogue types including task-oriented, chitchat and question-answering. Pictograms are a tool that is more and more used by people with cognitive or communication disabilities. Access scientific knowledge from anywhere. performance of state-of-the-art systems on this The hyperparameters are selected in the same, Since both the VUA and the TOEFL corpora are, annotated for metaphors, using one to help the, other during learning could potentially provide ad-, the data is from different types of texts and dif-. For example, Accept/Agree dialogue acts often occur with the Joy emotion, Apology with Sadness, and Thanking with Joy. Preparation for the EIT to books for. http://www.lrec-conf.org/proceedings/lrec2020/pdf/2020.lrec-1.18.pdf, Linguistic, Kinematic and Gaze Information in Task Descriptions: The LKG-Corpus, Tim Reinboth, Stephanie Gross, Laura Bishop and Brigitte Krenn. http://www.lrec-conf.org/proceedings/lrec2020/pdf/2020.lrec-1.78.pdf, PACO: a Corpus to Analyze the Impact of Common Ground in Spontaneous Face-to-Face Interaction, Mary Amoyal, Béatrice Priego-Valverde and Stephane Rauzy. Data from neuroscience and psychology suggest that sensorimotor cognition may be of central importance to language. The mechanism to transport the AC and to segment the auditory signal is based on Ɵ/γ-oscillations, where a Ɵ-cycle has the duration of a Ɵ-syllable. Motivated by this inexperience aspect, we aim to smooth the learning curve by teaching the novices to edit images using low-level command terminologies. http://www.lrec-conf.org/proceedings/lrec2020/pdf/2020.lrec-1.53.pdf, A Comparison of Explicit and Implicit Proactive Dialogue Strategies for Conversational Recommendation, Matthias Kraus, Fabian Fischbach, Pascal Jansen and Wolfgang Minker. A dialog system that can monitor the health status of seniors has a huge potential for solving the labor force shortage in the caregiving industry in aging societies. However, in the NLP literature, research on temporal expressions has focused mostly on data from the news, from the clinical domain, and from social media. The study contributes new insights to the human-agent interaction and the voice user interface design. annotated for metaphor. and (b) a corpus of medium to high quality timed, as a Foreign Language annotated under a different. The test results will serve as an initiative result for each Korean information extraction task and are expected to serve as a comparison target for various studies on Korean information extraction using the data collected in this study. The enhanced model achieved absolute improvements of up to 1.7 and 0.7 p.p. http://www.lrec-conf.org/proceedings/lrec2020/pdf/2020.lrec-1.8.pdf. "The FBI"). In this paper we provide a pilot neuroimaging study of the possible neural correlates of speech disfluencies perception, using a combination of the corpus and functional magnetic-resonance imaging (fMRI) methods. We implement a multilingual interactive agent in the field of healthcare and conduct experiments to illustrate the effectiveness of the implemented agent. We also generated simulated dialogues between dialogue policies and simulated users and asked MTurkers to rate them again on the same aspects. Structured interviews can be used to obtain this information, but are time-consuming and not scalable. Expressing emotion is known as an efficient way to persuade one’s dialogue partner to accept one’s claim or proposal. The voice assistant domain is very different than the typical domains that have been the focus of work on temporal expression identification, thus requiring a dedicated data collection. In contrast to traditional learner corpora, ReLCo is collected and annotated fully automatically, while students perform exercises using the Revita language-learning platform. It consists of 11 French face-to-face conversations lasting around 15 minutes each. Nowadays, spoken dialogue agents such as communication robots and smart speakers listen to narratives of humans. https://www.goodreads.com/author/show/4528259.Elena_Mihalkova Curation is improved using classifiers trained on textual data in Wikipedia articles on Hindu temples. As a result, it was demonstrated that annotated multichannel corpora like RUPEX can be an important resource for experimental research in interdisciplinary fields. The dataset consists of 117, fragments sampled across four genres from the, by approximately the same number of tokens, al-, though the number of texts differs greatly, The data is annotated using the MIP-VU proce-, dure with a strong inter-annotator reliability of, cult cases where a group of annotators could not, ered words marked as metaphors decided as such, and annotations is the same as the one used in, the first shared task on metaphor detection (, This data labeled for metaphor was sampled, from the publicly available ETS Corpus of Non-, say responses to eight persuaisve/argumentativ, prompts, for three native languages of the writer, (Japanese, Italian, Arabic), and for two proficiency, levels – medium and high. In French, most systems run different setups, making their comparison difficult. In this paper, we present an annotation methodology that is content- and technique- agnostic while associating note sentences to sets of dialogue sentences. To assess these factors, we conducted a usability study in which 42 participants perceive proactive voice output in a Wizard-of-Oz study in a driving simulator. Text-processing algorithms that annotate main components of a story-line are presently in great need of corpora and well-agreed annotation schemes. When the roles swap I have gone from being the one looked after (yes, even as a grown woman) to be the one to look after her. Additionally, gestures which express only one metaphor are not sufficient to explain the broad array of metaphoric gestures and metaphoric scenes that human speakers naturally produce. Correlating results of crowd and laboratory ratings reveals high applicability of crowdsourcing for the factors overall quality, grammaticality, non-redundancy, referential clarity, focus, structure & coherence, summary usefulness, and summary informativeness. More Buying Choices ... (3 Used & New offers) Paperback. http://www.lrec-conf.org/proceedings/lrec2020/pdf/2020.lrec-1.44.pdf, A Process-oriented Dataset of Revisions during Writing, Rianne Conijn, Emily Dux Speltz, Menno van Zaanen, Luuk Van Waes and Evgeny Chukharev-Hudilainen. Although there are some startup problems, the conversion task seems manageable for the languages tested so far. Afterwards, we run a comparison with a support vector machine and a recurrent neural network classifier. Therefore, we aim at providing a general design framework for multilingual interactive agents in specialized domains that, it is assumed, have small or non-existent dialogue corpora. That is, we analyze the effects of CR on six different embedding methods and evaluate them in the context of seven lexical-semantic evaluation tasks and instantiation/hypernymy detection. Recorded are audio, video, motion and eye-tracking data while participants perform an action and describe what they do. We propose to launch a project to produce cortical speech databases with cortical recordings synchronized with the speech signal allowing to decipher the articulatory code. Therefore, we provide an extensive dataset on revisions made during writing (accessible via https://hdl.handle.net/10411/VBDYGX). Ty - supermodel Cycle 2 Russian: Ты - супермодель 2 was the second Cycle of the Russian reality show on the STS TV channel, a competition of non - professional http://www.lrec-conf.org/proceedings/lrec2020/pdf/2020.lrec-1.19.pdf, The ACQDIV Corpus Database and Aggregation Pipeline, Anna Jancso, Steven Moran and Sabine Stoll. http://www.lrec-conf.org/proceedings/lrec2020/pdf/2020.lrec-1.16.pdf, Cortical Speech Databases For Deciphering the Articulatory Code. Nowadays Personal Assistants (PAs) are available in multiple environments and become increasingly popular to use via voice. We analyze the inverse feature weighting, and show that, across languages, grammatical morphemes get the lowest weights. in the text but are not detected by the system. 9th International Joint Conference on Natur, bidirectional transformers for language understand-. By stringing together chains of these simple blocks, complex thoughts and ideas can be conveyed. In this paper, we leverage dialogues with conversational agents, which contain strong suggestions of user information, to automatically extract user attributes. Our automated methods can be used to incorporate AMR into a larger NLU pipeline supporting human-robot dialogue. Join Facebook to connect with Elena Mikhalkova and others you may know. Previous computational work on ellipsis resolution has focused on one type of ellipsis, namely Verb Phrase Ellipsis (VPE) and a few other related phenomenon. Automatically-flagged candidate expressions were manually annotated for http://www.lrec-conf.org/proceedings/lrec2020/pdf/2020.lrec-1.68.pdf, The ISO Standard for Dialogue Act Annotation, Second Edition, Harry Bunt, Volha Petukhova, Emer Gilmartin, Catherine Pelachaud, Alex Fang, Simon Keizer and Laurent Prévot. We present a corpus of 240 argumentative es- We tested them, first, on the science fiction story ``We Can Remember It for You Wholesale'' by Philip K. Dick. Using the 17 English dialogs of the DialogBank as gold standard, our preliminary experiments have shown that including the mapped dialogs during the training phase leads to improved performance while recognizing communicative functions in the Task dimension. LREC 2020 was not held in Marseille this year and only the Proceedings were published. Argumentation-relevant metaphors in test-tak, ings of the 2018 Conference of the North Ameri-, can Chapter of the Association for Computational, Louisiana. face-to- face dialogues in which two people who meet for the first time talk with no particular purpose other than just talking. An important objective in health-technology is the ability to gather information about people's well-being. Developing a well-functioning TOIA involves several research areas: artificial intelligence, human-computer interaction, natural language processing, question answering, and dialogue systems. However, they are mainly used manually via workbooks, whereas caregivers and families would like to use more automated tools (use speech to generate pictograms, for example). Hill, Omer Levy, and Samuel R Bowman. In addition to spoken audio recordings available for both parts, camera recordings and skeleton-, facial expression- and eye-gaze tracking data have been collected for the lab-based part of the corpus. http://www.lrec-conf.org/proceedings/lrec2020/pdf/2020.lrec-1.77.pdf, EDA: Enriching Emotional Dialogue Acts using an Ensemble of Neural Annotators, Chandrakant Bothe, Cornelius Weber, Sven Magg and Stefan Wermter. The intrinsic and extrinsic quality evaluation is an essential part of the summary evaluation methodology usually conducted in a traditional controlled laboratory environment. We introduce in this paper a generic approach to combine implicit crowdsourcing and language learning in order to mass-produce language resources (LRs) for any language for which a crowd of language learners can be involved. In this paper, we introduce an architecture to simultaneously identify non-referring expressions (including expletives, predicative {\NP}s, and other types)  and build coreference chains, including singletons. Our main concerns were that vocabulary in language learning materials might be sparse, i.e. We annotated two accessible multi-modal emotion corpora: IEMOCAP and MELD. We present in this work a new dataset of coreference annotations for works of literature in English, covering 29,103 mentions in 210,532 tokens from 100 works of fiction published between 1719 and 1922. Paperback Tantsy marionetok. http://www.lrec-conf.org/proceedings/lrec2020/pdf/2020.lrec-1.20.pdf, Providing Semantic Knowledge to a Set of Pictograms for People with Disabilities: a Set of Links between WordNet and Arasaac: Arasaac-WN, Didier Schwab, Pauline Trial, Céline Vaschalde, Loïc Vial, Emmanuelle Esperanca-Rodier and Benjamin Lecouteux. are metaphors according to VUA ground truth, was not sufficiently offset by the increase in pre-, cision (although there is a small improvement in. Quantitative evaluations using 37,995 responsive utterances showed the appropriateness of the proposed classification. We develop the methodology using a two-step strategy. For example, the three underlined, words in the following sentence were classified as, metaphors by the version that was trained on VUA, ter augmentation with the TOEFL data: “A less di-, rect measure which is applicable only to the most, senior management is to observe the fall or rise of, the share price when a particular executiv. 2013. This framework uses semi-guided dialogue to avoid interactions that breach procedures and processes only known to experts, while enabling the capture of a wide variety of interactions. the context of political communication, marketing, cent interest in automated detection of metaphor, Metaphor Detection shared task held as a part of, corpus of well-edited BNC articles from a variety. First published in 2018 1 edition. 09/10/2018 ∙ by Ting-Yun Chang, et al. The robot partner was a humanoid Nao robot, and it was expected that its agent-like behaviour would render humanrobot interactions similar to human-human interaction but also high-light important differences due to the robot’s limited conversational capabilities. Secondly, it appears that the system has learned, some sentence-level characteristics of sentences, that contain figurative language, in that quite often, multiple words in the same sentence got tagged, is that of 4 new words in the same sentence being, Using idioms for an auxiliary task did not help, iom data instead of the TOEFL 11 idiom data; this, resulted in comparable performance, still without, version. This paper deals with the annotation of dialogue acts in a multimodal corpus of first encounter dialogues, i.e. We describe a computational However, standard sequence tagging models do not explicitly take advantage of linguistic theories of metaphor identification. We make the corpus and the platform freely available. To apply machine learning approaches to the development of the modules, we created large annotated datasets of 280,467 question-response pairs and 38,868 voluntary utterances. A common approach to this problem is to ask multiple reviewers to evaluate the same artifacts. We also set up some experiments to observe the effects of the responded utterance on the current utterance, and the correlation between emotion and relation types in emotion and relation classification tasks. as an auxiliary task for the main TOEFL task, in an improved performance on the TOEFL test, data but not on VUA data. We present results of initial experiments by various collaborators where we measure the time required to produce substantial LARA resources, up to the length of short novels, in Dutch, English, Farsi, French, German, Icelandic, Irish, Swedish and Turkish. same number (3,908) of sentences without idioms. JRC, First important LR player: First to adopt the ISLRN initiative, The ISLRN: an increasingly widespread persistent identifier, International Expert Meeting on Improving Access to Multilingual Cyberspace, STOA Workshop on Language Equality in the Digital Age, What’s new in the Directive on Copyright in the Digital Single Market, The General Data Protection Regulation (GDPR), EC adopts new standard license for online content, Special Interest Group: Under-resourced Languages, Collaborative Resource Construction & Crowdsourcing, Computer-Assisted Language Learning (CALL), Conversational Systems/Dialogue/Chatbots/Human-Robot Interaction, Legal Issues on Webcrawling Report available, ELRA LRs now indexed on Google Dataset Search and ELG LT Platform, LT4All Collection of Research Papers now available. We experiment with two DNN models which are inspired by two human metaphor identification procedures. Results show that the current model outperforms most recent works by 0.5%-11% F1, indicating the effectiveness of using modality norms for metaphor detection. Sag, and Thomas W, Pranav Rajpurkar, Jian Zhang, Konstantin Lop, error correction: Machine translation and classifiers, sociation for Computational Linguistics (V. Association for Computational Linguistics. This article presents a resource that links WordNet, the widely known lexical and semantic database, and Arasaac, the largest freely available database of pictograms. We also identified object segmentation as the key factor to user satisfaction. Winograd Schemas are particularly challenging anaphora resolution problems, designed to involve common sense reasoning and to limit the biases and artefacts commonly found in natural language understanding datasets. In addition, we applied neural machine translation (NMT) and statistical machine translation (SMT) techniques to correct the grammar of the JSL learners' sentences and evaluated their results using our corpus. Game bonbon quest. Revisions can be analyzed using a product-oriented approach (focusing on a finished product, the text that has been produced) or a process-oriented approach (focusing on the process that the writer followed to generate this product). Dramatic texts are a highly structured literary text type. These neural models annotate the emotion corpora with dialogue act labels, and an ensemble annotator extracts the final dialogue act label. The corpus provides valuable information about patterns of learner errors and can be used as a language resource for a number of research tasks, while its creation is much cheaper and faster than for traditional learner corpora. Multi-task transformer-based architectur, xchen002,cleong,mflor,bbeigmanklebanov@ets.org, This paper describes the ETS entry to the 2020, bution consists of a sequence of experiments, ening it by spell-correcting the TOEFL cor-, pus, followed by a multi-task learning set-, ting, where one of the tasks is the token-level. http://www.lrec-conf.org/proceedings/lrec2020/pdf/2020.lrec-1.84.pdf, The Brain-IHM Dataset: a New Resource for Studying the Brain Basis of Human-Human and Human-Machine Conversations, Magalie Ochs, Roxane Bertrand, Aurélie Goujon, Deirdre Bolger, Anne-Sophie Dubarry and Philippe Blache. Given that each task is performed and evaluated with a different dataset, analyzing the effect of the previous task on the next task with a single dataset throughout the information extraction process is impossible. Gerald Zaltman and Lindsay H Zaltman. http://www.lrec-conf.org/proceedings/lrec2020/pdf/2020.lrec-1.47.pdf, Toward a Paradigm Shift in Collection of Learner Corpora, Anisia Katinskaia, Sardana Ivanova and Roman Yangarber.