Search Results for author: Guillaume Bernard

Found 7 papers, 2 papers with code

Analyzing BERT Cross-lingual Transfer Capabilities in Continual Sequence Labeling

1 code implementation MMMPIE (COLING) 2022 Juan Manuel Coria, Mathilde Veron, Sahar Ghannay, Guillaume Bernard, Hervé Bredin, Olivier Galibert, Sophie Rosset

Knowledge transfer between neural language models is a widely used technique that has proven to improve performance in a multitude of natural language tasks, in particular with the recent rise of large pre-trained language models like BERT.

Continual Learning Cross-Lingual Transfer +6

Leveraging Historical Data for High-Dimensional Regression Adjustment, a Composite Covariate Approach

no code implementations26 Mar 2021 Samuel Branders, Alvaro Pereira, Guillaume Bernard, Marie Ernst, Adelin Albert

Within this context, we address the long-running question "What is the optimum number of covariates to include in a clinical trial?"

regression

Evaluate On-the-job Learning Dialogue Systems and a Case Study for Natural Language Understanding

no code implementations26 Feb 2021 Mathilde Veron, Sophie Rosset, Olivier Galibert, Guillaume Bernard

On-the-job learning consists in continuously learning while being used in production, in an open environment, meaning that the system has to deal on its own with situations and elements never seen before.

Natural Language Understanding

LNE-Visu : a tool to explore and visualize multimedia data

no code implementations JEPTALNRECITAL 2016 Guillaume Bernard, Juliette Kahn, Olivier Galibert, R{\'e}mi Regnier, S{\'e}verine Demeyer

LNE-Visu : a tool to explore and visualize multimedia data LNE-Visu is a tool to explore and visualize multimedia data created for the LNE evaluation campaigns.

Visu

FABIOLE, a Speech Database for Forensic Speaker Comparison

no code implementations LREC 2016 Moez Ajili, Jean-Fran{\c{c}}ois Bonastre, Juliette Kahn, Solange Rossato, Guillaume Bernard

A speech database has been collected for use to highlight the importance of {``}speaker factor{''} in forensic voice comparison.

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