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RETRIEVING SPEAKER INFORMATION FROM PERSONALIZED ACOUSTIC MODELS FOR SPEECH RECOGNITION
In: IEEE ICASSP 2022 ; https://hal.archives-ouvertes.fr/hal-03539741 ; IEEE ICASSP 2022, 2022, Singapour, Singapore (2022)
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2
An Overview of Indian Spoken Language Recognition from Machine Learning Perspective
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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3
One model for the learning of language.
In: Proceedings of the National Academy of Sciences of the United States of America, vol 119, iss 5 (2022)
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4
Thirty Years of Machine Translation in Language Teaching and Learning: A Review of the Literature
In: L2 Journal, vol 14, iss 1 (2022)
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5
Assessing the impact of OCR noise on multilingual event detection over digitised documents
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)
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6
MAGIC DUST FOR CROSS-LINGUAL ADAPTATION OF MONOLINGUAL WAV2VEC-2.0
In: ICASSP 2022 ; https://hal.archives-ouvertes.fr/hal-03544515 ; ICASSP 2022, May 2022, Singapour, Singapore (2022)
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7
Introducing the HIPE 2022 Shared Task: Named Entity Recognition and Linking in Multilingual Historical Documents
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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8
Can Character-based Language Models Improve Downstream Task Performance in Low-Resource and Noisy Language Scenarios?
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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9
Cross-lingual few-shot hate speech and offensive language detection using meta learning
In: ISSN: 2169-3536 ; EISSN: 2169-3536 ; IEEE Access ; https://hal.archives-ouvertes.fr/hal-03559484 ; IEEE Access, IEEE, 2022, 10, pp.14880-14896. ⟨10.1109/ACCESS.2022.3147588⟩ (2022)
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10
Annotation of Morphological Errors in L2 Russian Corpus Analysis
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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11
Cross-Situational Learning Towards Robot Grounding
In: https://hal.archives-ouvertes.fr/hal-03628290 ; 2022 (2022)
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12
Cross-Situational Learning Towards Robot Grounding
In: https://hal.archives-ouvertes.fr/hal-03628290 ; 2022 (2022)
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13
A Methodology for the Comparison of Human Judgments With Metrics for Coreference Resolution
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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14
Le modèle Transformer: un « couteau suisse » pour le traitement automatique des langues
In: Techniques de l'Ingenieur ; https://hal.archives-ouvertes.fr/hal-03619077 ; Techniques de l'Ingenieur, Techniques de l'ingénieur, 2022, ⟨10.51257/a-v1-in195⟩ ; https://www.techniques-ingenieur.fr/base-documentaire/innovation-th10/innovations-en-electronique-et-tic-42257210/transformer-des-reseaux-de-neurones-pour-le-traitement-automatique-des-langues-in195/ (2022)
Abstract: This paper presents an overview of the state of the art in natural language processing, exploring one specific computational architecture, the Transformer model, which plays a central role in a wide range of applications. This architecture condenses many advances in neural learning methods and can be exploited in many ways : to learn representations for linguistic entities ; to generate coherent utterances and answer questions; to perform utterance transformations, an illustration being their automatic translation. These different facets of the architecture will be successively presented, which will also allow us to discuss its limitations. ; Cet article présente un survol de l’état de l’art en traitement automatique des langues, en explorant une architecture computationnelle, le modèle Transformer, qui joue un rôle central dans une large gamme d’applications. Cette architecture condense de nombreuses avancées des méthodes d’apprentissage neuronales et peut être exploitée de multiples manières : pour apprendre à représenter les entités linguistiques ; pour générer des énoncés cohérents et répondre à des questions ; pour réaliser des transformations des énoncés, une illustration étant leur traduction automatique. Ces différentes facettes de l’architecture seront successivement présentées, ce qui permettra également d’évoquer ses limitations.
Keyword: [INFO.INFO-TT]Computer Science [cs]/Document and Text Processing; Apprentissage Automatique; Language Models; Machine Learning; Modèles de Langues; Natural Language Processing; Neural Machine Translation; Traduction automatique neuronale; Traitement Automatique des Langues
URL: https://doi.org/10.51257/a-v1-in195
https://hal.archives-ouvertes.fr/hal-03619077/file/Transformers.pdf
https://hal.archives-ouvertes.fr/hal-03619077/document
https://hal.archives-ouvertes.fr/hal-03619077
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15
The use of MT by undergraduate translation students for different learning tasks
In: https://hal.archives-ouvertes.fr/hal-03547415 ; 2022 (2022)
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16
Formulaic Expressions for Foreign Language Learning and Teaching
In: ISSN: 1615-3014 ; Linguistik Online ; https://hal.archives-ouvertes.fr/hal-03562566 ; Linguistik Online, Bern Open Publishing, 2022, Vermischtes/Miscellaneous, 113 (1), pp.91-110 ; https://bop.unibe.ch/linguistik-online (2022)
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17
КОНТРОЛЬ КАК ОСНОВА ЭФФЕКТИВНОГО ОБУЧЕНИЯ ИНОСТРАННОМУ ЯЗЫКУ СТУДЕНТОВ НЕЯЗЫКОВЫХ ВУЗОВ ... : CONTROL AS A BASIS FOR EFFECTIVE FOREIGN LANGUAGE TEACHING OF STUDENTS IN NON-LINGUISTIC UNIVERSITIES ...
И.Ф. Мусаелян. - : Мир науки, культуры, образования, 2022
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18
МОНОЛОГИЧЕСКАЯ РЕЧЬ С ТОЧКИ ЗРЕНИЯ УЧЁНЫХ ... : MONOLOGICAL SPEECH FROM THE POINT OF VIEW OF SCIENTISTS ...
Н. И. Шадманова. - : Academic research in educational sciences, 2022
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АКТУАЛЬНЫЕ ТЕНДЕНЦИИ ЦИФРОВИЗАЦИИ ИНОЯЗЫЧНОГО ОБУЧЕНИЯ В НЕЯЗЫКОВОМ ВУЗЕ ... : CURRENT TRENDS IN DIGITALIZATION OF FOREIGN LANGUAGE EDUCATION IN A NON-LINGUISTIC UNIVERSITY ...
Е.Б. Манахова. - : Мир науки, культуры, образования, 2022
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20
THE ROLE OF LISTENING IN LANGUAGE ACQUISITION; THE CHALLENGES & STRATEGIES IN TEACHING LISTENING ... : РОЛЬ СЛУШАНИЯ В ОФОРМЛЕНИИ ЯЗЫКА; ПРОБЛЕМЫ И СТРАТЕГИИ ОБУЧЕНИЯ АУДИРОВАНИЮ ...
Zokirova, Zulkhumor. - : Oriental renaissance: Innovative, educational, natural and social sciences, 2022
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