Search Results for author: Bassam Jabaian

Found 17 papers, 0 papers with code

Semantic enrichment towards efficient speech representations

no code implementations3 Jul 2023 Gaëlle Laperrière, Ha Nguyen, Sahar Ghannay, Bassam Jabaian, Yannick Estève

Over the past few years, self-supervised learned speech representations have emerged as fruitful replacements for conventional surface representations when solving Spoken Language Understanding (SLU) tasks.

Spoken Language Understanding

Findings from Experiments of On-line Joint Reinforcement Learning of Semantic Parser and Dialogue Manager with real Users

no code implementations25 Oct 2021 Matthieu Riou, Bassam Jabaian, Stéphane Huet, Fabrice Lefèvre

The analysis of these experiments gives us some insights, discussed in the paper, into the difficulty for the system's trainers to establish a coherent and constant behavioural strategy to enable a fast and good-quality training phase.

Dialogue Management Management +3

Where are we in semantic concept extraction for Spoken Language Understanding?

no code implementations24 Jun 2021 Sahar Ghannay, Antoine Caubrière, Salima Mdhaffar, Gaëlle Laperrière, Bassam Jabaian, Yannick Estève

More recent works on self-supervised training with unlabeled data open new perspectives in term of performance for automatic speech recognition and natural language processing.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +7

Joint On-line Learning of a Zero-shot Spoken Semantic Parser and a Reinforcement Learning Dialogue Manager

no code implementations1 Oct 2018 Matthieu Riou, Bassam Jabaian, Stéphane Huet, Fabrice Lefèvre

Several variants of joint learning are investigated and tested with user trials to confirm that the overall on-line learning can be obtained after only a few hundred training dialogues and can overstep an expert-based system.

Dialogue Management Management +3

Apprentissage en ligne interactif d'un g\'en\'erateur en langage naturel neuronal pour le dialogue homme-machine (On-line Interactive Learning of Natural Language Neural Generation for Human-machine)

no code implementations JEPTALNRECITAL 2017 Matthieu Riou, Bassam Jabaian, St{\'e}phane Huet, Fabrice Lef{\`e}vre

R{\'e}cemment, de nouveaux mod{\`e}les {\`a} base de r{\'e}seaux de neurones r{\'e}currents ont {\'e}t{\'e} propos{\'e}s pour traiter la g{\'e}n{\'e}ration en langage naturel dans des syst{\`e}mes de dialogue (Wen et al., 2016a).

Algorithmes de classification et d'optimisation: participation du LIA/ADOC á DEFT'14

no code implementations21 Feb 2017 Luis Adrián Cabrera-Diego, Stéphane Huet, Bassam Jabaian, Alejandro Molina, Juan-Manuel Torres-Moreno, Marc El-Bèze, Barthélémy Durette

This year, the DEFT campaign (D\'efi Fouilles de Textes) incorporates a task which aims at identifying the session in which articles of previous TALN conferences were presented.

General Classification

Automatic Corpus Extension for Data-driven Natural Language Generation

no code implementations LREC 2016 Elena Manishina, Bassam Jabaian, St{\'e}phane Huet, Fabrice Lef{\`e}vre

As data-driven approaches started to make their way into the Natural Language Generation (NLG) domain, the need for automation of corpus building and extension became apparent.

Text Generation

Compr\'ehension automatique de la parole sans donn\'ees de r\'ef\'erence

no code implementations JEPTALNRECITAL 2015 Emmanuel Ferreira, Bassam Jabaian, Fabrice Lef{\`e}vre

Cette m{\'e}thode combine une description ontologique minimale de la t{\^a}che vis{\'e}e avec l{'}utilisation d{'}un espace s{\'e}mantique continu appris par des approches {\`a} base de r{\'e}seaux de neurones {\`a} partir de donn{\'e}es g{\'e}n{\'e}riques non-annot{\'e}es.

dialog state tracking Zero-Shot Learning

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