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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 4 5...113 Hits 1 – 20 of 2.250 1 The contextual logic Kohler, Arnaud In: https://hal.archives-ouvertes.fr/hal-03195162 ; 2022 (2022) BASE Show details 2 Learning and controlling the source-filter representation of speech with a variational autoencoder Sadok, Samir; Leglaive, Simon; Girin, Laurent... In: https://hal.archives-ouvertes.fr/hal-03650569 ; 2022 (2022) BASE Show details 3 Assessing the impact of OCR noise on multilingual event detection over digitised documents Boros, Emanuela; Nguyen, Nhu Khoa; Lejeune, Gaël; Doucet, Antoine In: ISSN: 1432-5012 ; EISSN: 1432-1300 ; International Journal on Digital Libraries ; https://hal.archives-ouvertes.fr/hal-03635985 ; International Journal on Digital Libraries, Springer Verlag, 2022, ⟨10.1007/s00799-022-00325-2⟩ (2022) Abstract: International audience ; Event detection (ED) is a crucial task for natural language processing (NLP) and it involves the identification of instances of specified types of events in text and their classification into event types. The detection of events from digitised documents could enable historians to gather and combine a large amount of information into an integrated whole, a panoramic interpretation of the past. However, the level of degradation of digitised documents and the quality of the optical character recognition (OCR) tools might hinder the performance of an event detection system. While several studies have been performed in detecting events from historical documents, the transcribed documents needed to be hand-validated which implied a great effort of human expertise and manual labor-intensive work. Thus, in this study, we explore the robustness of two different event detection language-independent models to OCR noise, over two datasets that cover different event types and multiple languages. We aim at analysing their ability to mitigate problems caused by the low quality of the digitised documents and we simulate the existence of transcribed data, synthesised from clean annotated text, by injecting synthetic noise. For creating the noisy synthetic data, we chose to utilise four main types of noise that commonly occur after the digitisation process: Character Degradation, Bleed Through, Blur, and Phantom Character. Finally, we conclude that the imbalance of the datasets, the richness of the different annotation styles, and the language characteristics are the most important factors that can influence event detection in digitised documents. Keyword: [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]; [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; [INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC]; [INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR]; [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]; [INFO.INFO-TT]Computer Science [cs]/Document and Text Processing; Digitised Documents; Event Detection; Information Extraction URL: https://hal.archives-ouvertes.fr/hal-03635985/file/IJDL2022-Assessing%20the%20Impact%20of%20OCR%20Noise%20on%20Multilingual%20Event%20Detection%20over%20Digitised%20Documents.pdf https://doi.org/10.1007/s00799-022-00325-2 https://hal.archives-ouvertes.fr/hal-03635985/document https://hal.archives-ouvertes.fr/hal-03635985 BASE Hide details 4 Introducing the HIPE 2022 Shared Task: Named Entity Recognition and Linking in Multilingual Historical Documents Ehrmann, Maud; Romanello, Matteo; Doucet, Antoine... 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) BASE Show details 5 Can Character-based Language Models Improve Downstream Task Performance in Low-Resource and Noisy Language Scenarios? Riabi, Arij; Sagot, Benoît; Seddah, Djamé 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) BASE Show details 6 Annotation of Morphological Errors in L2 Russian Corpus Analysis Kor Chahine, Irina; Uetova, Ekaterina 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) BASE Show details 7 Cross-Situational Learning Towards Robot Grounding OOTA, Subba Reddy; Alexandre, Frédéric; Hinaut, Xavier In: https://hal.archives-ouvertes.fr/hal-03628290 ; 2022 (2022) BASE Show details 8 Cross-Situational Learning Towards Robot Grounding OOTA, Subba Reddy; Alexandre, Frédéric; Hinaut, Xavier In: https://hal.archives-ouvertes.fr/hal-03628290 ; 2022 (2022) BASE Show details 9 A Methodology for the Comparison of Human Judgments With Metrics for Coreference Resolution Borovikova, Mariya; Grobol, Loïc; Lefeuvre-Halftermeyer, Anaïs... In: HumEval at ACL ; https://hal.archives-ouvertes.fr/hal-03650294 ; HumEval at ACL, May 2022, Dublin, Ireland ; https://humeval.github.io/ (2022) BASE Show details 10 Can machines learn to see without visual databases? Betti, Alessandro; Gori, Marco; Melacci, Stefano... In: https://hal.archives-ouvertes.fr/hal-03526569 ; 2022 (2022) BASE Show details 11 A comparative study of several parameterizations for speaker recognition ... Faundez-Zanuy, Marcos. - : arXiv, 2022 BASE Show details 12 A Neural Pairwise Ranking Model for Readability Assessment ... Lee, Justin; Vajjala, Sowmya. - : arXiv, 2022 BASE Show details 13 Compiler-Driven Simulation of Reconfigurable Hardware Accelerators ... Li, Zhijing; Ye, Yuwei; Neuendorffer, Stephen. - : arXiv, 2022 BASE Show details 14 Subspace-based Representation and Learning for Phonotactic Spoken Language Recognition ... Lee, Hung-Shin; Tsao, Yu; Jeng, Shyh-Kang. - : arXiv, 2022 BASE Show details 15 ClassSPLOM -- A Scatterplot Matrix to Visualize Separation of Multiclass Multidimensional Data ... Aupetit, Michael; Ali, Ahmed. - : arXiv, 2022 BASE Show details 16 A Deep CNN Architecture with Novel Pooling Layer Applied to Two Sudanese Arabic Sentiment Datasets ... Mhamed, Mustafa; Sutcliffe, Richard; Sun, Xia. - : arXiv, 2022 BASE Show details 17 Mono vs Multilingual BERT: A Case Study in Hindi and Marathi Named Entity Recognition ... Litake, Onkar; Sabane, Maithili; Patil, Parth. - : arXiv, 2022 BASE Show details 18 Informative Causality Extraction from Medical Literature via Dependency-tree based Patterns ... Kabir, Md. Ahsanul; Almulhim, AlJohara; Luo, Xiao. - : arXiv, 2022 BASE Show details 19 Learning and controlling the source-filter representation of speech with a variational autoencoder ... Sadok, Samir; Leglaive, Simon; Girin, Laurent. - : arXiv, 2022 BASE Show details 20 Correcting Misproducted Speech using Spectrogram Inpainting ... Ben-Simon, Talia; Kreuk, Felix; Awwad, Faten. - : arXiv, 2022 BASE Show details Page: 1 2 3 4 5...113

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