| Téléchargement | - Voir la version finale : BRIGHTER: BRIdging the gap in human-annotated textual emotion recognition datasets for 28 languages (PDF, 1.5 Mio)
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| DOI | Trouver le DOI : https://doi.org/10.18653/v1/2025.acl-long.436 |
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| Auteur | Rechercher : Muhammad, Shamsuddeen Hassan; Rechercher : Ousidhoum, Nedjma; Rechercher : Abdulmumin, Idris; Rechercher : Wahle, Jan Philip; Rechercher : Ruas, Terry; Rechercher : Beloucif, Meriem; Rechercher : De Kock, Christine; Rechercher : Surange, Nirmal; Rechercher : Teodorescu, Daniela; Rechercher : Ahmad, Ibrahim Said; Rechercher : Adelani, David Ifeoluwa; Rechercher : Aji, Alham Fikri; Rechercher : Ali, Felermino D. M. A.; Rechercher : Alimova, Ilseyar; Rechercher : Araujo, Vladimir; Rechercher : Babakov, Nikolay; Rechercher : Baes, Naomi; Rechercher : Bucur, Ana-Maria; Rechercher : Bukula, Andiswa; Rechercher : Cao, Guanqun; Rechercher : Tufiño, Rodrigo; Rechercher : Chevi, Rendi; Rechercher : Chukwuneke, Chiamaka Ijeoma; Rechercher : Ciobotaru, Alexandra; Rechercher : Dementieva, Daryna; Rechercher : Gadanya, Murja Sani; Rechercher : Geislinger, Robert; Rechercher : Gipp, Bela; Rechercher : Hourrane, Oumaima; Rechercher : Ignat, Oana; Rechercher : Lawan, Falalu Ibrahim; Rechercher : Mabuya, Rooweither; Rechercher : Mahendra, Rahmad; Rechercher : Marivate, Vukosi; Rechercher : Panchenko, Alexander; Rechercher : Piper, Andrew; Rechercher : Ferreira, Charles Henrique Porto; Rechercher : Protasov, Vitaly; Rechercher : Rutunda, Samuel; Rechercher : Shrivastava, Manish; Rechercher : Udrea, Aura Cristina; Rechercher : Wanzare, Lilian Diana Awuor; Rechercher : Wu, Sophie; Rechercher : Wunderlich, Florian Valentin; Rechercher : Zhafran, Hanif Muhammad; Rechercher : Zhang, Tianhui; Rechercher : Zhou, Yi; Rechercher : Mohammad, Saif M.1Identifiant ORCID : https://orcid.org/0000-0003-2716-7516 |
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| Affiliation | - Conseil national de recherches Canada. Technologies numériques
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| Format | Texte, Article |
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| Conférence | The 63rd Annual Meeting of the Association for Computational Linguistics, July 27 - August 1, 2025, Vienna, Austria |
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| Résumé | People worldwide use language in subtle and complex ways to express emotions. Although emotion recognition–an umbrella term for several NLP tasks–impacts various applications within NLP and beyond, most work in this area has focused on high-resource languages. This has led to significant disparities in research efforts and proposed solutions, particularly for under-resourced languages, which often lack high-quality annotated datasets.In this paper, we present BRIGHTER–a collection of multi-labeled, emotion-annotated datasets in 28 different languages and across several domains. BRIGHTER primarily covers low-resource languages from Africa, Asia, Eastern Europe, and Latin America, with instances labeled by fluent speakers. We highlight the challenges related to the data collection and annotation processes, and then report experimental results for monolingual and crosslingual multi-label emotion identification, as well as emotion intensity recognition. We analyse the variability in performance across languages and text domains, both with and without the use of LLMs, and show that the BRIGHTER datasets represent a meaningful step towards addressing the gap in text-based emotion recognition. |
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| Date de publication | 2025-07-27 |
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| Maison d’édition | Association for Computational Linguistics |
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| Licence | |
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| Dans | |
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| Langue | anglais |
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| Publications évaluées par des pairs | Oui |
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| Exporter la notice | Exporter en format RIS |
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| Signaler une correction | Signaler une correction (s'ouvre dans un nouvel onglet) |
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| Identificateur de l’enregistrement | 9862cc79-bd09-45e4-b778-0950da509925 |
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| Enregistrement créé | 2025-09-18 |
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| Enregistrement modifié | 2025-09-19 |
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