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Multiagent Dynamics of Gradual Argumentation Semantics
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In: Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2022) ; 21st International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2022) ; https://hal.archives-ouvertes.fr/hal-03584238 ; 21st International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2022), May 2022, Auckland (virtual), New Zealand (2022)
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Psychiatry on Twitter: Content Analysis of the Use of Psychiatric Terms in French
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In: ISSN: 2561-326X ; JMIR Formative Research ; https://hal.archives-ouvertes.fr/hal-03614832 ; JMIR Formative Research, JMIR Publications 2022, 6 (2), pp.e18539. ⟨10.2196/18539⟩ ; https://formative.jmir.org/2022/2/e18539 (2022)
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Emotional Speech Recognition Using Deep Neural Networks
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In: ISSN: 1424-8220 ; Sensors ; https://hal.archives-ouvertes.fr/hal-03632853 ; Sensors, MDPI, 2022, 22 (4), pp.1414. ⟨10.3390/s22041414⟩ (2022)
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From Biological Synapses to “Intelligent” Robots
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In: ISSN: 2079-9292 ; Electronics ; https://hal.archives-ouvertes.fr/hal-03590998 ; Electronics, MDPI, 2022, 11 (5), pp.707. ⟨10.3390/electronics11050707⟩ (2022)
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| 6 |
Multiagent Dynamics of Gradual Argumentation Semantics
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In: Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2022) ; 21st International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2022) ; https://hal.archives-ouvertes.fr/hal-03584238 ; 21st International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2022), May 2022, Auckland (virtual), New Zealand (2022)
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Question-Based Explainability in Abstract Argumentation
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In: https://hal-univ-tlse3.archives-ouvertes.fr/hal-03647896 ; [Research Report] IRIT/RR--2022--01--FR, IRIT : Institut de Recherche en Informatique de Toulouse, France. 2022, pp.1-64 (2022)
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Meta-Analysis of the Functional Neuroimaging Literature with Probabilistic Logic Programming
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In: https://hal.archives-ouvertes.fr/hal-03590714 ; 2022 (2022)
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| 9 |
An investigation of English-Irish machine translation and associated resources
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Dowling, Meghan. - : Dublin City University. School of Computing, 2022. : Dublin City University. ADAPT, 2022
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In: Dowling, Meghan orcid:0000-0003-1637-4923 (2022) An investigation of English-Irish machine translation and associated resources. PhD thesis, Dublin City University. (2022)
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Abstract:
As an official language in both Ireland and the European Union (EU), there is a high demand for English-Irish (EN-GA) translation in public administration. The difficulty that translators currently face in meeting this demand leads to the need for reliable domain-specific user-driven EN-GA machine translation (MT). This landscape provides a timely opportunity to address some research questions surrounding MT for the EN-GA language pair. To this end, we assess the corpora available for training data-driven MT systems, including publicly-available data, data collected through EU-supported data collection efforts and web-crawling, showing that though Irish is a low-resource language it is possible to increase the corpora available through concerted data collection efforts. We investigate how increased corpora affect domain-specific (public administration) statistical MT (SMT) and neural MT (NMT) systems using automatic metrics. The effect that different SMT and NMT parameters have on these automatic values is also explored, using sentence-level metrics to identify specific areas where output differs greatly between MT systems and providing a linguistic analysis of each. With EN-GA SMT and NMT automatic evaluation scores showing inconclusive results, we investigate the usefulness of EN-GA hybrid MT through the use of monolingual data as a source of artificial data creation via backtranslation. We evaluate these results using automatic metrics and linguistic analysis. Although results indicate that the addition of artificial data did not have a positive impact on EN-GA MT, repeated experiments involving Scottish Gaelic show that the method holds promise, given suitable conditions. Finally, given that the intended use-case of EN-GA MT is in the workflow of a professional translator, we conduct an in-depth human evaluation study for EN-GA SMT and NMT, providing a human-derived assessment of EN-GA MT quality and comparison of EN-GA SMT and NMT. We include a survey of translator opinions and recommendations surrounding EN-GA SMT and NMT as well as an analysis of data gathered through the post-editing of MT output. We compare these results to those generated automatically and provide recommendations for future work on EN-GA MT, in particular with regards to its use in a professional translation workflow within public administration.
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Keyword:
Artificial intelligence; Computational linguistics; Linguistics; Machine learning; Machine translating; Translating and interpreting
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URL: http://doras.dcu.ie/26574/
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| 10 |
Towards combined semantic and lexical scores based on a new representation of textual data to extract experimental data from scientific publications
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In: ISSN: 1751-5858 ; EISSN: 1751-5866 ; International Journal of Intelligent Information and Database Systems ; https://hal.inrae.fr/hal-03616243 ; International Journal of Intelligent Information and Database Systems, Inderscience, 2022, 15 (1), pp.78. ⟨10.1504/IJIIDS.2022.120146⟩ (2022)
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| 11 |
Integrating a Phrase Structure Corpus Grammar and a Lexical-Semantic Network: the HOLINET Knowledge Graph
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In: Proceedings of LREC 2022 ; https://hal-amu.archives-ouvertes.fr/hal-03655636 ; Proceedings of LREC 2022, Jun 2022, Marseille, France (2022)
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| 12 |
Caveats of Measuring Semantic Change of Cognates and Borrowings using Multilingual Word Embeddings
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In: LChange'22 - 3rd International Workshop on Computational Approaches to Historical Language Change 2022 ; https://hal.inria.fr/hal-03635005 ; LChange'22 - 3rd International Workshop on Computational Approaches to Historical Language Change 2022, May 2022, Dublin, Ireland (2022)
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| 13 |
Multistream neural architectures for cued-speech recognition using a pre-trained visual feature extractor and constrained CTC decoding
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In: ICASSP 2022 - IEEE International Conference on Acoustics, Speech and Signal Processing ; https://hal.archives-ouvertes.fr/hal-03578503 ; ICASSP 2022 - IEEE International Conference on Acoustics, Speech and Signal Processing, May 2022, Singapour, Singapore (2022)
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| 14 |
DeepL et Google Translate face à l'ambiguïté phraséologique
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In: https://hal.archives-ouvertes.fr/hal-03583995 ; 2022 (2022)
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| 15 |
An Overview of Indian Spoken Language Recognition from Machine Learning Perspective
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In: ISSN: 2375-4699 ; EISSN: 2375-4702 ; ACM Transactions on Asian and Low-Resource Language Information Processing ; https://hal.inria.fr/hal-03616853 ; ACM Transactions on Asian and Low-Resource Language Information Processing, ACM, In press, ⟨10.1145/3523179⟩ (2022)
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| 16 |
The contextual logic
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In: https://hal.archives-ouvertes.fr/hal-03195162 ; 2022 (2022)
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Morphology in the Corsican Language Database (BDLC) : assessment and perspectives ; La morphologie dans la Banque de Données Langue Corse : bilan et perspectives
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In: ISSN: 1638-9808 ; EISSN: 1765-3126 ; Corpus ; https://hal.archives-ouvertes.fr/hal-03591866 ; Corpus, Bases, Corpus, Langage - UMR 7320, 2022, Corpus et données en morpholgie, ⟨10.4000/corpus.7115⟩ ; https://journals.openedition.org/corpus/7115 (2022)
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Automatic generation of the complete vocal tract shape from the sequence of phonemes to be articulated
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In: ISSN: 0167-6393 ; EISSN: 1872-7182 ; Speech Communication ; https://hal.univ-lorraine.fr/hal-03650212 ; Speech Communication, Elsevier : North-Holland, 2022, ⟨10.1016/j.specom.2022.04.004⟩ (2022)
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VEREINDEUTIGUNG ZUR KLASSIFIZIERUNG LEXIKALISCHER OBJEKTE ; DISAMBIGUATION FOR THE CLASSIFICATION OF LEXICAL ITEMS ; DÉSAMBÏGUISATION POUR LA CLASSIFICATION DE LEXÈMES
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In: https://hal.archives-ouvertes.fr/hal-03598242 ; France, Patent n° : EP3937059A1. 2022 (2022)
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