| | Position : Postdoc / engineer - 12 months, Bordeaux
Starting date : 01/10/2018
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Profile : Speech processing, machine learning, artificial intelligence
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Location : primary : Computer Science Research Laboratory (LaBRI)
secondary : SANPSY (Sleep - Addiction - Neuropsychatry)
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Supervisors : Jean-Luc Rouas - LaBRI : jean-luc.rouas@labri.fr - main contact
Jean-Philippe Domenger - LaBRI
Pierre Philip - SANPSY
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Project : 'IS-OSA' (Innovative digital solution for personalised treatment of sleep apnea syndrome) funded by the Nouvelle Aquitaine Region
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Project summary :
Sleep deprivation have a strong impact on physical and mental health leading to multiple consequences: increase of heart failure rates, cognitive and behavorial troubles... In addition to the clinical interviews, it is possible to measure the fatigue state using several cues : eye movement, EEG data, behavorial expression data (e.g. body movements). It is however nowadays feasible, thanks to recent advances in speech processing, to characterise fatigue states using only speech related cues. This technique have the main advantage that it does not require any specific or invasive apparatus and could thus be carried out in diverse enviroments, out of clinical context.
The project aims at following patients suffering from sleep apnea syndrome by using the data collected during interviews with a virtual doctor. This data will complement other data collection sources such as measurements from CPAP devices.
The aim of this work is to focus on vocal cues characterising excessive daytime sleepiness in order to determine which are the vocal biomarkers of these troubles that could be integrated in the clinical measurements carried out during interviews with virtual doctors developped at SANPSY.
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Work plan:
- Carry out Audio and Video recordings of patients on-site at the hospital in Bordeaux
- Define the vocal parameters allowing to describe the troubles induced by excessive daytime sleepiness, in close collaboration with the SANPSY Lab.
- Study these parameters and use them in a excessive daytime sleepiness automatic classification framework using sleepiness measurements proposed by the clinical staff as ground truth.
- Implement the classification system in the virtual doctor framework developped at SANPSY and carry out clinical trials to validate the approach.
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Required skills:
- Training (PhD or Master internship) in automatic speech processing, contributions in analysis/features for speech signals are expected
- Machine learning and Artifical Intelligence : good knowledge of standard techniques (such as GMM/HMM/LDA) and knowledge/keen interest in deep learning methods
- Good programming skills in python, C/C++
- Interest for clinical research / collaboration with clinical staff (flexible hours)
- Good command of professionnal english
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Salary : according to diploma and experience (examples : Master+3y = 2137? gross/month, PhD+3y = 2511 ? gross/month)
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How to apply : Send your CV + cover letter + referees names + reports (interships,thesis,...) or publications by email to jean-luc.rouas@labri.fr |
