Jean-Pierre Lorré

TL;DR: This paper aims at using business models to design a logical model of a solution (logical architecture) as a principal step to reach the final collaborative solution and presents the theoretical aspects of this subject and the dedicated transformation rules.

TL;DR: This work proposes a new Deep Neural Network (DNN) speech recognition architecture which takes advantage from both DA and EM approaches in order to improve the prediction accuracy of the system.

TL;DR: This paper develops a knowledge-based system (KbS) which is composed of three main parts: knowledge gathering, knowledge representation and reasoning, and collaborative business process modelling and develops a prototype of the KbS, a computer-aided design tool of the CBP.

TL;DR: This article proposed a graph-based framework for abstractive meeting speech summarization that is fully unsupervised and does not rely on any annotations, which combines the strengths of multiple recent approaches while addressing their weaknesses.

TL;DR: A novel graph-based framework for abstractive meeting speech summarization that is fully unsupervised and does not rely on any annotations to take exterior semantic knowledge into account, and to design custom diversity and informativeness measures.