In collaborative learning environments, effective intelligent learning systems need to
accurately analyze and understand the collaborative discourse between learners (ie, group …

Due to the growth of technology, the expansion of communication infrastructure and crises of
COVID-19 pandemic, e-learning and virtual education is expanding. One of the best ways to …

Abstract Conventionally, Automatic Speech Recognition (ASR) systems are evaluated on
their ability to correctly recognize each word contained in a speech signal. In this context, the …

Evaluating automatic speech recognition (ASR) systems is a classical but difficult and still
open problem, which often boils down to focusing only on the word error rate (WER) …

This paper offers a comparative evaluation of four commercial ASR systems which are
evaluated according to the post-editing effort required to reach “publishable” quality and …

The performance of end-to-end automatic speech recognition (ASR) systems enables their
increasing integration into numerous applications. While there are various benefits to such …

L'évaluation de transcriptions issues de systèmes de Reconnaissance Automatique de la
Parole (RAP) est un problème difficile et toujours ouvert, qui se résume généralement à ne …

We propose a new setting for question answering (QA) in which users can query the system
using both natural language and direct interactions within a graphical user interface that …

Cette thèse s' inscrit dans le cadre d'une étude sur le potentiel de la transcription
automatique pour l'instrumentation de situations pédagogiques. Notre contribution porte sur …

This paper presents a French multimodal educational dataset of oral courses. This corpus is
part of the PASTEL (Performing Automated Speech Transcription for Enhancing Learning) …