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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 Hits 1 – 3 of 3 1 EVOLEX : la reconnaissance vocale au service du diagnostic des dysfonctionnements langagiers Petiot, Jim; Gravellier, Lila; Jucla, Mélanie... In: Séminaire AFCP 2021 – Phonétique Clinique ; https://hal-univ-tlse3.archives-ouvertes.fr/hal-03269242 ; Séminaire AFCP 2021 – Phonétique Clinique, May 2021, Toulouse (virtuel), France ; http://www.afcp-parole.org/seminaire-afcp-phonetique-clinique-27-mai-2021/ (2021) BASE Show details 2 Weakly supervised discourse segmentation for multiparty oral conversations Gravellier, Lila; Hunter, Julie; Muller, Philippe; Pellegrini, Thomas; Ferrané, Isabelle In: 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP 2021) ; https://hal.archives-ouvertes.fr/hal-03466161 ; 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP 2021), ACL: Association for Computational Linguistics, Nov 2021, Punta Cana, Dominican Republic. pp.1381-1392 ; https://aclanthology.org/2021.emnlp-main.104/ (2021) Abstract: International audience ; Discourse segmentation, the first step of discourse analysis, has been shown to improve results for text summarization, translation and other NLP tasks. While segmentation models for written text tend to perform well, they are not directly applicable to spontaneous, oral conversation, which has linguistic features foreign to written text. Segmentation is less studied for this type of language, where annotated data is scarce, and existing corpora more heterogeneous. We develop a weak supervision approach to adapt, using minimal annotation, a state of the art discourse segmenter trained on written text to French conversation transcripts. Supervision is given by a latent model bootstrapped by manually defined heuristic rules that use linguistic and acoustic information. The resulting model improves the original segmenter, especially in contexts where information on speaker turns is lacking or noisy, gaining up to 13% in F-score. Evaluation is performed on data like those used to define our heuristic rules, but also on transcripts from two other corpora. Keyword: [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL] URL: https://hal.archives-ouvertes.fr/hal-03466161/document https://hal.archives-ouvertes.fr/hal-03466161 https://hal.archives-ouvertes.fr/hal-03466161/file/Weakly_supervised_discourse_segmentation_of_speech_conversations_with_audio_and_text_features__Emnlp21_.pdf BASE Hide details 3 Weakly supervised discourse segmentation for multiparty oral conversations ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Ferrané, Isabelle; Gravellier, Lila. - : Underline Science Inc., 2021 BASE Show details

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