Amine Sehili

• Data Scientist
• Analyst at Cardiologs

Affect bursts play an important role in non-verbal social interaction. Laughter and smile are some of the most important social markers in human-robot social interaction. Not only do they contain affective information, they also may reveal the user’s communication strategy. In the context of human robot interaction, an automatic laughter and smile...

Social Signal Processing such as laughter or emotion detection is a very important issue, particularly in the field of human-robot interaction (HRI). At the moment, very few studies exist on elderly-people’s voices and social markers in real-life HRI situations. This paper presents a cross-corpus study with two realistic corpora featuring elderly p...

We present automatic systems that implement multimodal social dialogues involving humour with the humanoid robot Nao for the 16th Interspeech conference. Humorous capabilities of the systems are based on three main techniques: riddles, challenging the human participant, and punctual interventions. The presented prototypes will automatically record...

The challenge of this study is twofold: recognizing emotions from audio signals in naturalistic Human-Robot Interaction (HRI) environment, and using a cross-dataset recognition for robustness evaluation. The originality of this work lies in the use of six emotional models in parallel, generated using two training corpora and three acoustic feature...

Dans un contexte d'interaction homme-machine, les systèmes de détection des émo-tions dans la voix doivent être robustes aux variabilités et efficaces en temps de calcul. Cet article présente les performances que nous pouvons obtenir en utilisant uniquement des indices paraverbaux (nonverbaux). Nous proposons une méthodologie pour sélectionner les...

In a Human-Machine Interaction context, automatic in-voice affective state detection systems have to be robust to variabilities and computationally efficient. This paper presents the performance that can be reached using para-verbal (non-verbal) cues. We propose a methodology to select robust parameters families, based on the study of three sets of...

In many human-robot social interactions, where the robot is to interact with only one human throughout the interaction, the " human " side of a conversation is very likely to interact with other humans present in the same room and temporarily loses the focus on the main interaction. These human-human interactions can be a very brief chat or a prett...

This paper presents a corpus featuring social interaction between elderly people in a retirement home and the humanoid robot Nao. This data collection is part of the French project ROMEO2 that follows the ROMEO project. The goal of the project is to develop a humanoid robot that can act as a comprehensive assistant for persons suffering from loss o...

In a Human-Machine Interaction context, automatic in-voice affective state detection systems have to be robust to variabilities and computationally efficient. This paper presents the performance that can be reached using para-verbal (non-verbal) cues. We propose a methodology to select robust parameters families, based on the study of three sets of...

The SWEET-HOME1 project aims at providing audio-based interaction technology that lets the user have full control over their home environment and at detecting distress situations. This paper presents the audio analysis system PATSH developed for this project and a user experiment in a smart home that evaluates the performances of the first revision...

In many countries around the world, the number of elderly people living alone has been increasing. In the last few years, a significant number of research projects on elderly people monitoring have been launched. Most of them make use of several modalities such as video streams, sound, fall detection and so on, in order to monitor the activities of...

This study aims at providing audio-based interaction tech-nology that lets the users have full control over their home environment, at detecting distress situations and at easing the social inclusion of the elderly and frail population. The paper presents the sound and speech analysis system evaluated thanks to a corpus of data acquired in a real s...

This paper presents a medical remote monitoring application which aims at detecting falls. The detection system is based on three modalities: a wearable sensor, infrared sensors and a sound analysis module. The sound analysis is presented briefly. The multimodal fusion is made using the Dempster Schaffer theory through Evidential Network. A first e...

Most elderly people monitoring systems include the detection of abnormal situations, in particular distress situations, as one of their main goals. In order to reach this objective, many so-lutions end up combining several modalities such as video tra-cking, fall detection and sound recognition, so as to increase the reliability of the system. In t...

The Sweet-Home project aims at providing audio-based interaction technology that lets the user have full control over their home environment, at detecting distress situations and at easing the social inclusion of the elderly and frail population. This paper presents an overview of the project focusing on the multimodal sound corpus acquisition and...

Research in the field of face recognition knew considerable progress during these last years. Among the most evoked techniques we find those which employ the optimization of the size of the data in order to get a representation which makes it possible to carry out the recognition. For these methods, the images of faces are seen like points in a spa...

The advent of modern communications and the low cost of some kinds of devices have resulted in a desire to equip elderly peoples' homes with sensors to monitor their activities and be forewarned of abnormal situations. In such an environment, sound may represent a rich source of information that can be exploited and this is considered as one of the...