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Magalie Ochs <[log in to unmask]>
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Magalie Ochs <[log in to unmask]>
Fri, 20 Apr 2018 12:02:19 +0200
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*PhD fellowship*

/Computational model of conversational behaviors integrating behavioral 
and physiological data from human-human and human-machine interactions/


/Laboratoire d’Informatique et des Systèmes (LIS) et Laboratoire Parole 
et Langage (LPL) /

Aix-Marseille Université & CNRS

*_Keywords:_* conversational speech, multimodal data analysis, 
neurophysiological data, machine learning, artificial agents.

The PhD project is part of an A*MIDEX project /PhysSocial/ that aims at 
a betterunderstanding of the specificities of social interactions by 
comparing relationships between behavior and neurophysiologyin 
human‐human and human‐robot discussion. The goal of the PhD is toanalyze 
the multimodal signals (speech, eyes direction, physiological, and 
neurophysiologic signals) from conversational activity using signal 
processing and machine learning methodologies in order to compare the 
human-human and human-robot interactions.

The PhD is organized around 3 main tasks:

  * /Multimodal data preprocessing/: in a first step, the objective is
    to process the row data (speech, transcribed speech, eyes tracking,
    physiological and neurophysiological signals) corresponding to
    human-human and human-robot conversation in order to extract time
    series corresponding to behavioral features, as well as cognitive
    events derived from local activity in well-defined brain areas
    involved inlanguage and social cognition
  * /Machine learning of causal relations: /in a second step,//time
    series will be used by statistical learning to identify causal
    relations between behavioral and physiological features and
    cognitive events extracted from neurophysiological recording with
    fMRI. From a learning point of view, one challenge in this project
    is the high-dimensional data. We address this issue with a focus on
    the features representation and selection problems.
  * /Computational modeling and implementation in a humanoid robot/: the
    last step consists in integrating the knowledge extracted from the
    data sets into an existing platform (Furhat talking head) in order
    to generate the appropriate behavior (speech and eyes behavior) of
    the artificial agent during an interaction with an user. The model
    will be evaluated through a experimentation that will be conducted
    in collaboration with the other partners of the project.

The PhD candidate should have a master's degree completed in Computer 
Science, Applied Mathematics, Signal or Natural Language Processing 
(with solid background in machine learning).

The candidate should have a strong background in machine learning and 
signal processing with a focus on multimodality. Some complementary 
previous experience would be appreciated in the following topics:
• Multimodal data processing
• Data science applied to language data
• Dialogue systems

The PhD is fully funded during 3 years as part of the A*MIDEX 
interdisciplinary project PhysSocial, including personalized training, 
travel expenses, and conferences attendance.

French language is not required.

Aix Marseille University (, the largest French 
University, is ideally located on the Mediterranean coast, and only 1h30 
away from the Alps.

The application files consists of the following documents:
- A detailed curriculum,
- A description of the academic background and copy of academic records 
and most recent diploma,
- A cover letter describing why the applicant wishes to participate in 
this project, a justification of the inter-disciplinary of her/his 
research, his/her training project and career Plan including these 
dimensions, and his/her research’s adequacy with the proposed topics
- 2 recommendation letters (including one from the master or equivalent 
diploma supervisor)

The application files should be sent to :
Laurent Prévot: [log in to unmask] 
<mailto:[log in to unmask]>
Magalie Ochs: [log in to unmask] <mailto:[log in to unmask]>

For any question, contact :

Laurent Prévot: [log in to unmask] 
<mailto:[log in to unmask]>*prevot* <*prevot*>

Magalie Ochs: [log in to unmask] <mailto:[log in to unmask]>

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