PhD position in Opinion Analysis in human-agent interactions

Telecom ParisTech [1]

46 rue Barrault  75013 Paris ? France

Starting date: from Now to Early Autumn 2018

Possibility to start with an internship during first semester 2018.

Duration of the PhD funding: 36 months

*Position description* 

The PhD student will take part in the ANR JCJC MAOI (Multimodal Analysis of Opinions in Interactions) at Telecom-ParisTech. He/She will tackle the following challenging issue: the integration of opinion mining methods in human-agent interactions (i.e. companion robots or virtual vocal assistants such as Siri, Google Now, Cortana, etc.)

The role of the PhD will consist in developing machine learning methods for the multimodal (i.e. speech and text) analysis of the user?s opinion during his/her interaction with an agent. The main challenge will be to integrate the interaction context in machine-learning opinion detection methods. 

The work will include:

- the development of machine learning/deep learning approaches (Conditional Random Fields, Long-Short-Term-Memory networks)

- the integration of complex and interactional linguistic features in machine-learning models for the detection of opinions in interactions

- the integration of acoustic features in multimodal models

- the evaluation of the system in interaction context.

The PhD will join the Social Computing topic [2] in the S2a group [3] at Telecom-ParisTech.

Selected references for this position from [4] :

Barriere, V., Clavel, C., and Essid, E. (2017). Opinion dynamics modeling for movie review transcripts classification with hidden conditional random fields. Interspeech.

Clavel, C.; Callejas, Z., Sentiment analysis: from opinion mining to human-agent interaction, Affective Computing, IEEE Transactions on, 7.1 (2016): 74-93

Langlet, C. and Clavel, C. (2015). Improving social relationships in face-to-face human-agent interactions: when the agent wants to know user?s likes and dislikes. In ACL, Beijin, China.

Langlet, C. and Clavel, C. (2016). Grounding the detection of the user?s likes and dislikes on the topic structure of human-agent interactions. Knowledge-Based Systems.

* Candidate profile*

As a minimum requirement, the successful candidate will have:

?    A master degree or equivalent in one or more of the following areas: machine

learning, natural language processing, affective computing

?    Excellent programming skills (preferably in Python)

?    Good command of English

The ideal candidate will also (optionally) have:

?    Knowledge in natural language processing

?    Knowledge in probabilistic graphical models and deep learning

-- More about the position

?    Place of work: Paris, France

?    For more information about Telecom ParisTech see [1]

-- How to apply

Applications are to be sent to Chloé Clavel [4]

The application should be formatted as a single pdf file and should include:

?    A complete and detailed curriculum vitae

?    A letter of motivation

?    The transcript of grades  

?    The names and addresses of two referees

[1] https://www.telecom-paristech.fr/eng/  

[2] https://www.tsi.telecom-paristech.fr/recherche/themes-de-recherche/analyse-automatique-des-donnees-sociales-social-computing/ 

[3] http://www.tsi.telecom-paristech.fr/ssa/# 

[4] https://clavel.wp.imt.fr/publications/