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MAGIC DUST FOR CROSS-LINGUAL ADAPTATION OF MONOLINGUAL WAV2VEC-2.0
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In: ICASSP 2022 ; https://hal.archives-ouvertes.fr/hal-03544515 ; ICASSP 2022, May 2022, Singapour, Singapore (2022)
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Probing Multilingual Cognate Prediction Models
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In: Findings of the Association for Computational Linguistics: ACL 2022 ; https://hal.inria.fr/hal-03614691 ; Findings of the Association for Computational Linguistics: ACL 2022, May 2022, Dublin, Ireland (2022)
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Introducing the HIPE 2022 Shared Task: Named Entity Recognition and Linking in Multilingual Historical Documents
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In: Advances in Information Retrieval. 44th European Conference on IR Research, ECIR 2022, Stavanger, Norway, April 10–14, 2022, Proceedings, Part II ; https://hal.archives-ouvertes.fr/hal-03635971 ; Matthias Hagen; Suzan Verberne; Craig Macdonald; Christin Seifert; Krisztian Balog; Kjetil Nørvåg; Vinay Setty. Advances in Information Retrieval. 44th European Conference on IR Research, ECIR 2022, Stavanger, Norway, April 10–14, 2022, Proceedings, Part II, 13186, Springer International Publishing, pp.347-354, 2022, Lecture Notes in Computer Science, 978-3-030-99738-0. ⟨10.1007/978-3-030-99739-7_44⟩ (2022)
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Can Character-based Language Models Improve Downstream Task Performance in Low-Resource and Noisy Language Scenarios?
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In: Seventh Workshop on Noisy User-generated Text (W-NUT 2021, colocated with EMNLP 2021) ; https://hal.inria.fr/hal-03527328 ; Seventh Workshop on Noisy User-generated Text (W-NUT 2021, colocated with EMNLP 2021), Jan 2022, punta cana, Dominican Republic ; https://aclanthology.org/2021.wnut-1.47/ (2022)
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Automatic Speech Recognition and Query By Example for Creole Languages Documentation
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In: Findings of the Association for Computational Linguistics: ACL 2022 ; https://hal.archives-ouvertes.fr/hal-03625303 ; Findings of the Association for Computational Linguistics: ACL 2022, May 2022, Dublin, Ireland (2022)
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| 26 |
Annotation of Morphological Errors in L2 Russian Corpus Analysis
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In: 21st Annual Second Language Acquisition and Teaching Interdisciplinary Roundtable ; https://hal.archives-ouvertes.fr/hal-03620469 ; 21st Annual Second Language Acquisition and Teaching Interdisciplinary Roundtable, University of Arizona, Feb 2022, Tucson, United States (2022)
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| 27 |
Intelligibility and comprehensibility: A Delphi consensus study
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In: ISSN: 1368-2822 ; EISSN: 1460-6984 ; International Journal of Language and Communication Disorders ; https://hal.archives-ouvertes.fr/hal-03543198 ; International Journal of Language and Communication Disorders, Wiley, 2022, 57 (1), pp.21 - 41. ⟨10.1111/1460-6984.12672⟩ ; https://onlinelibrary.wiley.com/doi/10.1111/1460-6984.12672 (2022)
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Cross-Situational Learning Towards Robot Grounding
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In: https://hal.archives-ouvertes.fr/hal-03628290 ; 2022 (2022)
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Cross-Situational Learning Towards Robot Grounding
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In: https://hal.archives-ouvertes.fr/hal-03628290 ; 2022 (2022)
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PROTECT: A Pipeline for Propaganda Detection and Classification
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In: CLiC-it 2021- Italian Conference on Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-03417019 ; CLiC-it 2021- Italian Conference on Computational Linguistics, Jan 2022, Milan, Italy (2022)
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Abstract:
International audience ; Propaganda is a rhetorical technique to present opinions with the deliberate goal of influencing the opinions and the actions of other (groups of) individuals for predetermined misleading ends. The employment of such manipulation techniques in politics and news articles, as well as its subsequent spread on social networks, may lead to threatening consequences for the society and its more vulnerable members. In this paper, we present PROTECT (PROpaganda Text dEteCTion), a new system to automatically detect propagandist messages and classify them along with the propaganda techniques employed. PROTECT is designed as a full pipeline to firstly detect propaganda text snippets from the input text, and then classify the technique of propaganda, taking advantage of semantic and argumentation features. A video demo of the PROTECT system is also provided to show its main functionalities. ; La propaganda è una tecnica retorica per presentare determinate opinioni con l'obiettivo deliberato di influenzare le opinioni e le azioni di altri (gruppi di) individui per fini predeterminati e tendenzialmente fuorvianti. L'impiego di tale tecnica di manipolazione in politica e nella stampa, così come la sua diffusione sulle reti sociali, può portare a conseguenze disastrose per la società e per i suoi membri più vulnerabili. In questo articolo presentiamo PROTECT (PROpaganda Text dEteCTion), un nuovo sistema per identificare automaticamente i messaggi propagandistici e classificarli rispetto alle tecniche di propaganda utilizzate. PROTECT è un sistema progettato come una pipeline completa per rilevare in primo luogo i frammenti di testo propagandistici dato il testo proposto, e successivamente classificare tali frammenti secondo la tecnica di propaganda usata, sfruttando le caratteristiche semantiche e argomentative del testo. Questo articolo presenta anche un video dimostrativo del sistema PROTECT per mostrare le principali funzionalità fornite all'utente.
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Keyword:
[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]; [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; [INFO.INFO-TT]Computer Science [cs]/Document and Text Processing; Argumentation; Natural Language Processing; Propaganda Detection; Sentiment Analysis
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URL: https://hal.archives-ouvertes.fr/hal-03417019v2/file/CLiC_it_2021__demo_propaganda_snippets_and_techniques_classification.pdf
https://hal.archives-ouvertes.fr/hal-03417019
https://hal.archives-ouvertes.fr/hal-03417019v2/document
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| 31 |
PROTECT - A Pipeline for Propaganda Detection and Classification
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In: Eighth Italian Conference on Computational Linguistics (CLIC-it 2021) ; https://hal.archives-ouvertes.fr/hal-03417019 ; Eighth Italian Conference on Computational Linguistics (CLIC-it 2021), Jan 2022, Milan, Italy (2022)
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A Methodology for the Comparison of Human Judgments With Metrics for Coreference Resolution
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In: HumEval at ACL ; https://hal.archives-ouvertes.fr/hal-03650294 ; HumEval at ACL, May 2022, Dublin, Ireland ; https://humeval.github.io/ (2022)
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Building infrastructure for annotating medieval, classical and pre-orthographic languages: the Pyrrha ecosystem
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In: Digital Humanities 2022 (DH2022) ; https://hal.archives-ouvertes.fr/hal-03606756 ; Digital Humanities 2022 (DH2022), Jul 2022, Tokyo, Japan ; https://dh2022.adho.org/ (2022)
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Language identification, a tool for Corsican and for the evaluation of linguistic resources ; L'identification de langue, un outil au service du corse et de l'évaluation des ressources linguistiques
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In: Traitement Automatique des Langues ; https://hal.archives-ouvertes.fr/hal-03633290 ; Traitement Automatique des Langues, 2022, Diversité Linguistique, 62 (3), pp.13-37 ; https://www.atala.org/content/diversité-linguistique-linguistic-diversity-natural-language-processing (2022)
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| 35 |
Between History and Natural Language Processing: Study, Enrichment and Online Publication of French Parliamentary Debates of the Early Third Republic (1881-1899)
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In: ParlaCLARIN III at LREC2022 - Workshop on Creating, Enriching and Using Parliamentary Corpora ; https://hal.archives-ouvertes.fr/hal-03623351 ; ParlaCLARIN III at LREC2022 - Workshop on Creating, Enriching and Using Parliamentary Corpora, Jun 2022, Marseille, France ; https://www.clarin.eu/ParlaCLARIN-III (2022)
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| 36 |
Annoter et prédire des représentations linguistiques de phrases
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In: https://hal.archives-ouvertes.fr/tel-03544267 ; Informatique et langage [cs.CL]. Université de Paris, 2022 (2022)
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| 37 |
Predicting and Critiquing Machine Virtuosity: Mawwal Accompaniment as Case Study
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In: International Computer Music Conference ; https://hal.archives-ouvertes.fr/hal-03044066 ; International Computer Music Conference, Jul 2021, Santiago, Chile (2021)
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Investigating alignment interpretability for low-resource NMT
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In: ISSN: 0922-6567 ; EISSN: 1573-0573 ; Machine Translation ; https://hal.archives-ouvertes.fr/hal-03139744 ; Machine Translation, Springer Verlag, 2021, ⟨10.1007/s10590-020-09254-w⟩ (2021)
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End-to-end speaker segmentation for overlap-aware resegmentation
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In: Interspeech 2021 ; https://hal-univ-lemans.archives-ouvertes.fr/hal-03257524 ; Interspeech 2021, Aug 2021, Brno, Czech Republic ; https://www.interspeech2021.org/ (2021)
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Impact of Encoding and Segmentation Strategies on End-to-End Simultaneous Speech Translation
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In: INTERSPEECH 2021 ; https://hal.archives-ouvertes.fr/hal-03372487 ; INTERSPEECH 2021, Aug 2021, Brno, Czech Republic (2021)
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