5 citations · 8 across the 8 of their papers we have counts for
10 papers
Open-Source Large Language Models as Multilingual Crowdworkers: Synthesizing Open-Domain Dialogues in Several Languages With No Examples in Targets and No Machine Translation
Ahmed Njifenjou, Virgile Sucal, Bassam Jabaian +1
The prevailing paradigm in the domain of Open-Domain Dialogue agents predominantly focuses on the English language, encompassing both models and datasets. Furthermore, the financia…
FlowAct: A Proactive Multimodal Human-robot Interaction System with Continuous Flow of Perception and Modular Action Sub-systems
Timothée Dhaussy, Bassam Jabaian, Fabrice Lefèvre
The evolution of autonomous systems in the context of human-robot interaction systems necessitates a synergy between the continuous perception of the environment and the potential…
Language Portability Strategies for Open-domain Dialogue with Pre-trained Language Models from High to Low Resource Languages
Ahmed Njifenjou, Virgile Sucal, Bassam Jabaian +1
In this paper we propose a study of linguistic portability strategies of large pre-trained language models (PLMs) used for open-domain dialogue systems in a high-resource language…
Role-Play Zero-Shot Prompting with Large Language Models for Open-Domain Human-Machine Conversation
Ahmed Njifenjou, Virgile Sucal, Bassam Jabaian +1
Recently, various methods have been proposed to create open-domain conversational agents with Large Language Models (LLMs). These models are able to answer user queries, but in a o…
A dual task learning approach to fine-tune a multilingual semantic speech encoder for Spoken Language Understanding
Gaëlle Laperrière, Sahar Ghannay, Bassam Jabaian +1
Self-Supervised Learning is vastly used to efficiently represent speech for Spoken Language Understanding, gradually replacing conventional approaches. Meanwhile, textual SSL model…
Semantic enrichment towards efficient speech representations
Gaëlle Laperrière, Ha Nguyen, Sahar Ghannay +2
Over the past few years, self-supervised learned speech representations have emerged as fruitful replacements for conventional surface representations when solving Spoken Language…
Findings from Experiments of On-line Joint Reinforcement Learning of Semantic Parser and Dialogue Manager with real Users
Matthieu Riou, Bassam Jabaian, Stéphane Huet +1
Design of dialogue systems has witnessed many advances lately, yet acquiring huge set of data remains an hindrance to their fast development for a new task or language. Besides, tr…
Where are we in semantic concept extraction for Spoken Language Understanding?
Sahar Ghannay, Antoine Caubrière, Salima Mdhaffar +3
Spoken language understanding (SLU) topic has seen a lot of progress these last three years, with the emergence of end-to-end neural approaches. Spoken language understanding refer…
A Data Efficient End-To-End Spoken Language Understanding Architecture
Marco Dinarelli, Nikita Kapoor, Bassam Jabaian +1
End-to-end architectures have been recently proposed for spoken language understanding (SLU) and semantic parsing. Based on a large amount of data, those models learn jointly acous…
Joint On-line Learning of a Zero-shot Spoken Semantic Parser and a Reinforcement Learning Dialogue Manager
Matthieu Riou, Bassam Jabaian, Stéphane Huet +1
Despite many recent advances for the design of dialogue systems, a true bottleneck remains the acquisition of data required to train its components. Unlike many other language proc…