PhD position in Feature Function Learning for Sentiment Analysis in speech interactions

Telecom ParisTech (http://www.telecom-paristech.fr/eng/)
46 rue Barrault  75013 Paris - France

Advisors: 
Chloé Clavel  (http://clavel.wp.mines-telecom.fr/)
Slim Essid  (http://perso.telecom-paristech.fr/~essid/)

Starting date: Early Autumn 2015

Funding: Secured with the Telecom ParisTech Machine Learning for Big Data Chair (http://machinelearningforbigdata.telecom-paristech.fr) 

Keywords: Sentiment Analysis, Opinion Mining, Deep Learning, Conditional Random Fields, Natural Language Processing, Speech Processing, Natural Language Processing

Applications are invited for a 36 month PhD.

Topic: 
Sentiment analysis and opinion mining have gained an increasing interest with the explosion of textual content conveying users? opinions (e.g. film reviews, forum debates, tweets). Hence, natural language processing researchers have dedicated a great deal of effort into the development of methods amenable to opinion detection in such texts, though often simplifying the problem to one of classification over the valence (positive vs negative) and intensity axes. As for sentiment analysis in speech signals, there have been hardly any attempts. Further challenges are posed in this case where not only should the special features of spoken language be taken into account, but also prosodic features and the potential errors of automatic speech recognition systems.

The research work planned will focus on the development of sentiment analysis methods in the context of speech interactions (phone conversations, face-to-face human-agent interactions). The privileged research direction will consist in creating effective computational models of appraisal expressions. In particular, Conditional Random Fields and deep learning approaches will be considered with feature functions encoding the semantic rules usually used for our task.

IDEAL CANDIDATE: 
Master?s student or Master?s degree with background in
-        Machine learning / pattern recognition
-        Speech processing, natural language processing
-        Excellent programming skills (Python, Java, C/C++)
-        Good English level

APPLICATIONS:
To be sent to chloe.clavel@telecom-paristech.fr, slim.essid@telecom-paristech.fr,:
-        Curriculum Vitae
-        Statement of interest (in the body of the email)
-        Academic records
-        List of references

Incomplete applications will not be considered.