Search Results for author:
Found 11 papers, 2 papers with code
QUEER@DEFT2021 : Identification du Profil Clinique de Patients et Notation Automatique de Copies d’Étudiants (QUEER@DEFT2021 : Patients Clinical Profile Identification and Automatic Student Grading )
Dans la tâche d’identification de de profil clinique (tâche 1) nous présentons une méthode de recherche d’information basé sur un index dérivé du MeSH.
Stylo@DEFT2022 : Notation automatique de copies d’étudiant·e·s par combinaisons de méthodes de similarité (Stylo@DEFT2022 : Automatic short answer grading by combinations of similarity methods )
Cet article présente la participation de l’équipe STyLO (STIH, L3I, OBTIC) au DÉfi Fouille de Textes 2022 (DEFT 2022).
L3i at SemEval-2022 Task 11: Straightforward Additional Context for Multilingual Named Entity Recognition
Also, we consider that using additional contexts from the training set could improve the performance of a NER on short texts.
A Comprehensive Survey of Document-level Relation Extraction (2016-2023)
Document-level relation extraction (DocRE) is an active area of research in natural language processing (NLP) concerned with identifying and extracting relationships between entities beyond sentence boundaries.
Yes but.. Can ChatGPT Identify Entities in Historical Documents?
Large language models (LLMs) have been leveraged for several years now, obtaining state-of-the-art performance in recognizing entities from modern documents.
Extending Text Informativeness Measures to Passage Interestingness Evaluation (Language Model vs. Word Embedding)
In this paper we define the concept of Interestingness as a generalization of Informativeness, whereby the information need is diverse and formalized as an unknown set of implicit queries.
Audio Summarization with Audio Features and Probability Distribution Divergence
Our method, based on an extractive summarization approach, aims to select the most relevant segments until a time threshold is reached.
Étude de l'informativité des transcriptions : une approche basée sur le résumé automatique
In this paper we propose a new approach to evaluate the informativeness of transcriptions coming from Automatic Speech Recognition systems.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
WiSeBE: Window-based Sentence Boundary Evaluation
Do standard evaluation metrics like precision, recall, F-score or classification error; and more important, evaluating an automatic system against a unique reference is enough to conclude how well a SBD system is performing given the final application of the transcript?
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+5
Sentence Boundary Detection for French with Subword-Level Information Vectors and Convolutional Neural Networks
All three models have good F1 scores reaching values over 0. 97 regarding the "not sentence boundary" class.
Efficient Social Network Multilingual Classification using Character, POS n-grams and Dynamic Normalization
In this paper we describe a dynamic normalization process applied to social network multilingual documents (Facebook and Twitter) to improve the performance of the Author profiling task for short texts.
