Frédéric Aman


2016

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The CIRDO Corpus: Comprehensive Audio/Video Database of Domestic Falls of Elderly People
Michel Vacher | Saïda Bouakaz | Marc-Eric Bobillier Chaumon | Frédéric Aman | R. A. Khan | Slima Bekkadja | François Portet | Erwan Guillou | Solange Rossato | Benjamin Lecouteux
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

Ambient Assisted Living aims at enhancing the quality of life of older and disabled people at home thanks to Smart Homes. In particular, regarding elderly living alone at home, the detection of distress situation after a fall is very important to reassure this kind of population. However, many studies do not include tests in real settings, because data collection in this domain is very expensive and challenging and because of the few available data sets. The C IRDO corpus is a dataset recorded in realistic conditions in D OMUS , a fully equipped Smart Home with microphones and home automation sensors, in which participants performed scenarios including real falls on a carpet and calls for help. These scenarios were elaborated thanks to a field study involving elderly persons. Experiments related in a first part to distress detection in real-time using audio and speech analysis and in a second part to fall detection using video analysis are presented. Results show the difficulty of the task. The database can be used as standardized database by researchers to evaluate and compare their systems for elderly person’s assistance.

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Ecological Gestures for HRI: the GEE Corpus
Maxence Girard-Rivier | Romain Magnani | Véronique Aubergé | Yuko Sasa | Liliya Tsvetanova | Frédéric Aman | Clarisse Bayol
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

As part of a human-robot interaction project, we are interested by gestural modality as one of many ways to communicate. In order to develop a relevant gesture recognition system associated to a smart home butler robot. Our methodology is based on an IQ game-like Wizard of Oz experiment to collect spontaneous and implicitly produced gestures in an ecological context. During the experiment, the subject has to use non-verbal cues (i.e. gestures) to interact with a robot that is the referee. The subject is unaware that his gestures will be the focus of our study. In the second part of the experiment, we asked the subjects to do the gestures he had produced in the experiment, those are the explicit gestures. The implicit gestures are compared with explicitly produced ones to determine a relevant ontology. This preliminary qualitative analysis will be the base to build a big data corpus in order to optimize acceptance of the gesture dictionary in coherence with the “socio-affective glue” dynamics.

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CirdoX: an on/off-line multisource speech and sound analysis software
Frédéric Aman | Michel Vacher | François Portet | William Duclot | Benjamin Lecouteux
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

Vocal User Interfaces in domestic environments recently gained interest in the speech processing community. This interest is due to the opportunity of using it in the framework of Ambient Assisted Living both for home automation (vocal command) and for call for help in case of distress situations, i.e. after a fall. C IRDO X, which is a modular software, is able to analyse online the audio environment in a home, to extract the uttered sentences and then to process them thanks to an ASR module. Moreover, this system perfoms non-speech audio event classification; in this case, specific models must be trained. The software is designed to be modular and to process on-line the audio multichannel stream. Some exemples of studies in which C IRDO X was involved are described. They were operated in real environment, namely a Living lab environment.

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Acquisition et reconnaissance automatique d’expressions et d’appels vocaux dans un habitat. (Acquisition and recognition of expressions and vocal calls in a smart home)
Michel Vacher | Benjamin Lecouteux | Frédéric Aman | François Portet | Solange Rossato
Actes de la conférence conjointe JEP-TALN-RECITAL 2016. volume 1 : JEP

Cet article présente un système capable de reconnaître les appels à l’aide de personnes âgées vivant à domicile afin de leur fournir une assistance. Le système utilise une technologie de Reconnaissance Automatique de la Parole (RAP) qui doit fonctionner en conditions de parole distante et avec de la parole expressive. Pour garantir l’intimité, le système s’exécute localement et ne reconnaît que des phrases prédéfinies. Le système a été évalué par 17 participants jouant des scénarios incluant des chutes dans un Living lab reproduisant un salon. Le taux d’erreur de détection obtenu, 29%, est encourageant et souligne les défis à surmonter pour cette tâche.

2015

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Recognition of Distress Calls in Distant Speech Setting: a Preliminary Experiment in a Smart Home
Michel Vacher | Benjamin Lecouteux | Frédéric Aman | Solange Rossato | François Portet
Proceedings of SLPAT 2015: 6th Workshop on Speech and Language Processing for Assistive Technologies

2013

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Analyzing the Performance of Automatic Speech Recognition for Ageing Voice: Does it Correlate with Dependency Level?
Frédéric Aman | Michel Vacher | Solange Rossato | François Portet
Proceedings of the Fourth Workshop on Speech and Language Processing for Assistive Technologies

2012

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Contribution à l’étude de la variabilité de la voix des personnes âgées en reconnaissance automatique de la parole (Contribution to the study of elderly people’s voice variability in automatic speech recognition) [in French]
Frédéric Aman | Michel Vacher | Solange Rossato | François Portet
JEP-TALN-RECITAL 2012, Workshop ILADI 2012: Interactions Langagières pour personnes Agées Dans les habitats Intelligents (ILADI 2012: Language Interaction for Elderly in Smart Homes)

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Etude de la performance des modèles acoustiques pour des voix de personnes âgées en vue de l’adaptation des systèmes de RAP (Assessment of the acoustic models performance in the ageing voice case for ASR system adaptation) [in French]
Frédéric Aman | Michel Vacher | Solange Rossato | Remus Dugheanu | François Portet | Juline le Grand | Yuko Sasa
Proceedings of the Joint Conference JEP-TALN-RECITAL 2012, volume 1: JEP