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Impact Analysis of the Use of Speech and Language Models Pretrained by Self-Supersivion for Spoken Language Understanding.

, , , , , , , and . LREC, page 2949-2956. European Language Resources Association, (2022)

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End-To-End Named Entity And Semantic Concept Extraction From Speech., , , , , , and . SLT, page 692-699. IEEE, (2018)Error Analysis Applied to End-to-End Spoken Language Understanding., , , , , , and . ICASSP, page 8514-8518. IEEE, (2020)Dialogue History Integration into End-to-End Signal-to-Concept Spoken Language Understanding Systems., , , , and . ICASSP, page 8509-8513. IEEE, (2020)Curriculum d'apprentissage : reconnaissance d'entités nommées pour l'extraction de concepts sémantiques (Curriculum learning : named entity recognition for semantic concept extraction)., , , , and . PFIA (Articles longs), page 85-98. ATALA, (2019)Africa-Centric Self-Supervised Pre-Training for Multilingual Speech Representation in a Sub-Saharan Context., and . CoRR, (2024)Investigating Adaptation and Transfer Learning for End-to-End Spoken Language Understanding from Speech., , and . INTERSPEECH, page 824-828. ISCA, (2019)Représentation de la parole multilingue par apprentissage auto-supervisé dans un contexte subsaharien., and . TALN (JEP), page 163-172. ATALA and AFPC, (2024)Du signal au concept : réseaux de neurones profonds appliqués à la compréhension de la parole. (From signal to concept: Deep neural networks applied to spoken language understanding).. University of Maine, Le Mans, France, (2021)End2End Acoustic to Semantic Transduction., , , , , , and . ICASSP, page 7448-7452. IEEE, (2021)Recent Advances in End-to-End Spoken Language Understanding., , , , and . SLSP, volume 11816 of Lecture Notes in Computer Science, page 44-55. Springer, (2019)