January 2021 – Laboratoire Informatique d’Avignon

PhD defense of Randa Abdelmonem – 26 January 2021

26 January 2021

Date: Tuesday 26 January 2021 at 9:00 AM. Title: Quality of Service and Privacy in Internet of Things Dedicated to Healthcare Jury: Abstract: The Internet of Things (IoT) based healthcare systems usually composed of medical and environmental sensors, remote servers, and the network. These systems focus on providing remote monitoring, disease diagnosis, and treatment progress observation. The healthcare systems in IoT domain helps in realizing long-term economical, ubiquitous, and patient centered care systems, that result in improving treatment and patient outcomes. This research contributes to the domain by proposing a Cloud-Fog based architecture that can embrace multiple healthcare scenarios, and able to adapt dynamically with the context and status of the patients. It allows the mobility and physical activity of the patients in the environment through deployment and implementation of an appropriate Received Signal Strength (RSS) based handoff mechanism. It also proposes a mobility-aware task scheduling and allocation approach in cloud-fog computing paradigm, called MobMBAR, with the objective of minimizing the total schedule time (makespan). MobMBAR performs dynamic balanced healthcare tasks distribution between the cloud and fog devices. It is a data locality based approach that depends on changing the location where the data is computed to where it actually resides. Plus d'infos

PhD defense of Mayeul Matthias – 22 January 2021

2 January 2021

On January 22, 2021, Mayeul Matthias will defend his thesis entitled “Recommendation of Personalized Cultural Paths – An Interdisciplinary Study of Automated Visit Proposals.” This thesis is supervised by Juan-Manuel Torres and Didier Josselin, and co-supervised by Fen Zhou. The jury consists of: Abstract: This thesis focuses on recommending cultural visits through an interdisciplinary approach. These works combine techniques from Operations Research and natural language processing while drawing on concepts from audience sociology and geography. We propose new methods for evaluating cultural points of interest and automatically creating tourist routes that take into account the desires expressed by a visitor. These principles are applied on two different scales and contexts: museum visits and cultural paths within a city. In the first part, we concentrate on visits to art museums based on the preferences expressed by the visitor and the prestige of the artworks. This dual approach allows classifying the works both according to the cultural affinities of the visitor and their importance within the museum. The latter is calculated by applying automatic text summarization algorithms to the museum’s official descriptions of the works, providing a visit profile reflecting the discovery of a museum through its masterpieces. This profile can then Plus d'infos

H2020 SELMA Project

1 January 2021

Stream Learning for Multilingual Knowledge Transfer The internet contains vast amounts of data and information in various languages, both written and audiovisual. There’s an increasing need to leverage this largely untapped resource. The SELMA project, funded by the EU, focuses on ingesting and monitoring large quantities of data. It systematically trains machine learning models to perform tasks in natural language and utilizes these models to monitor data streams, aiming to enhance multilingual media monitoring and real-time content production. Ultimately, the project will advance cutting-edge techniques in language modeling, automatic translation, speech recognition, and synthesis. Project Coordinator: Deutsche Welle, DE Scientific Lead for LIA: Yannick ESTEVE Start Date: 01/01/2021 End Date: 30/12/2023 More

ANR muDialBot Project

1 January 2021

MUlti-party perceptually-active situated DIALog for human-roBOT interaction In muDialBot, our ambition is to proactively incorporate human-like behavioral traits in human-robot spoken communication. We aim to reach a new stage in harnessing the rich information provided by audio and visual data streams from humans. In particular, extracting verbal and non-verbal events should enhance the decision-making abilities of robots to manage turns of speech more naturally and also switch from group interactions to face-to-face dialogues according to the situation. There has been growing interest recently in companion robots capable of assisting individuals in their daily lives and effectively communicating with them. These robots are perceived as social entities, and their relevance to health and psychological well-being has been highlighted in studies. Patients, their families, and healthcare professionals will better appreciate the potential of these robots as certain limitations are quickly overcome, such as their ability to move, see, and listen to communicate naturally with humans, beyond what touchscreen displays and voice commands already enable. The scientific and technological outcomes of the project will be implemented on a commercial social robot and tested and validated with multiple use cases in the context of a day hospital unit. Large-scale data collection will complement in-situ Plus d'infos

H2020 ESPERANTO Project

1 January 2021

Exchanges for SPEech ReseArch aNd TechnOlogies Speech processing technologies are crucial for numerous commercial applications. The ESPERANTO project, funded by the EU, aims to make the next generation of AI algorithms used in speech processing applications more accessible. For instance, they should consider human involvement and be interpretable to allow sensitive applications and safeguard personal data. ESPERANTO envisions disseminating these technologies across European SMEs, expanding and ensuring their implementation for forensic, healthcare, and educational purposes. The project will support the development of freely accessible tools, conduct seminars on various speech processing themes to assist new students, researchers, and engineers working in speech AI, and contribute to the collection and sharing of linguistic and speech-related resources. Project Coordinator: University of Le Mans, FR Scientific Manager for LIA: Jean-François Bonastre Start Date: 01/01/2021 End Date: 30/06/2025 More