Keywords: Natural language understanding, decision support system, smart
home

The Laboratoire d'Informatique de Grenoble (LIG) of the University
Grenoble Alpes, Grenoble, France invites applications for a PhD position
in Computational Linguistics for Ambient Intelligence.

University of Grenoble Alpes is situated in a high-tech city located at
the heart of the Alps, in outstanding scientific and natural
surroundings. It is 3h by train from Paris ; 2h from Geneva and is less
than 1h from Lyon international airport.

The position starts in September 2017 and ends in July 2020 and is
proposed in the context of the national project Vocadom
(http://vocadom.imag.fr/) whose aim is to build technologies that make
natural hand-free speech interaction with a home automation system
possible from anywhere in the home even in adverse conditions
[Vacher2015].

The aim of the PhD will be to build a new generation of situated spoken
human machine interaction where uttered sentences by a human are
understood within the context of the interaction in the home. The
targeted application is a distant speech hand free and ubiquitous voice
user interface to make the home automation system react to voice
commands [Chahuara2017]. The system should be able to process possibly
erroneous outputs from an ASR system (Automatic Speech Recognition) to
extract meaning related to a voice command and to decide about which
command to execute or to send a relevant feed-back to the user. The
challenge will be to constantly adapt the system to new lexical phrases
(no a priori grammar), new situations (e.g., unseen user, context) and
change in the house (e.g., new device, device out of order). In this
work, we propose to extend classical S/NLU (Natural Language
Understanding) approaches by including non-linguistic contextual
information in the NLU process to tackle the ambiguity and borrow
zero-shot learning techniques [Ferreira2015] to extend the lexical space
on-line. Reinforcement learning is targeted to adapt the models to the
user(s) all along the use of the system [Mnih2015].  The candidate will
be strongly encouraged to publish their progress to the main events of
the field (ACL, Interspeech, Ubicomp).  The PhD candidate will also be
involved in experiments including real smart-home and real users
(elderly people and people with visual impairment) [Vacher2015].

REFERENCES :
[Mnih2015] Mnih, Kavukcuoglu et al.  Human-level control through deep
reinforcement learning. Nature 518, 529?533

[Chahuara2017] Chahuara, F. Portet, M. Vacher Context-aware decision
making under uncertainty for voice-based control of smart home Expert
Systems with Applications, Elsevier, 2017, 75, pp.63-79.

[Ferreira2015] E Ferreira, B Jabaian, F Lefevre Online adaptative
zero-shot learning spoken language understanding using word-embedding
Acoustics, Speech and Signal Processing (ICASSP), 2015

[Vacher2015] M. Vacher, S. Caffiau, F. Portet, B. Meillon, C. Roux, E.
Elias, B. Lecouteux, P. Chahuara. Evaluation of a context-aware voice
interface for Ambient Assisted Living: qualitative user study vs.
quantitative system evaluation. ACM - Transactions on Speech and
Language Processing, Association for Computing Machinery, 2015,
pp.5:1-5:36.

JOB REQUIREMENTS AND QUALIFICATIONS

- Master?s degree in Computational Linguistics or Artificial
Intelligence (Computer Science can also be considered)
- Solid programming skills,
- Good background in machine learning,
- Excellent English communication and writing skills,
- Good command of French (mandatory),
- Experience in experimentation involving human participants would be a
   plus
- Experience in dialogue systems would be a plus plus

Applications should include:

- Cover letter outlining interest in the position
- Names of two referees
- Curriculum Vitae (CV) (with publications if applicable)
- Copy of the university marks (grade list)

and be sent to michel.vacher@imag.fr and francois.portet@imag.fr

Research Group Website : http://getalp.imag.fr
Research project website : http://vocadom.imag.fr/