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[AUDITORY] 1-year research position on deep learning for distant-mic speech recognition
Dear list,
We are offering a 1-year postdoc/R&D engineer position on distant-mic
speech recognition in the context of a large-scale R&D project on voice
control of home appliances involving 5 companies and 3 academic labs.
The successful candidate will conduct research on state-of-the-art
acoustic model adaptation and contribute to transfer his/her ideas into
a commercial ASR product. More specifically, we are interested in
adapting DNN acoustic models to reveberation and noise conditions by
exloring deep learning-based uncertainty propagation techniques in the
line of [1,2].
Ideal start: March 2016 (possible until June)
Salary: 2600 to 3300 €/month gross depending on experience, plus free
health insurance and additional benefits
Ideal profile:
- MSc or PhD in speech processing, machine learning, audio signal
processing, or applied statistics
- proficient programming in C++, shell, Matlab/Python
- experience with Kaldi and deep learning software
To apply: send a CV, a motivation letter, a list of publications, and
one or more recommendation letters to emmanuel.vincent@xxxxxxxx and
irina.illina@xxxxxxxx.
Applications will be assessed on a continuous basis until Jan 15. Please
apply as soon as possible before that date.
PS: if you happen to be at ASRU this week and you're interested by this
position, please come and say hello.
References:
[1] A.H. Abdelaziz, S. Watanabe, J.R. Hershey, E. Vincent, D. Kolossa,
"Uncertainty propagation through deep neural networks", Interspeech 2015.
[2] Y. Tachioka, S. Watanabe, "Uncertainty training and decoding methods
of deep neural networks based on stochastic representation of enhanced
features", Interspeech 2015.
--
Emmanuel Vincent
PAROLE Project-Team
Inria Nancy - Grand Est
615 rue du Jardin Botanique, 54600 Villers-lès-Nancy, France
Phone: +33 3 8359 3083 - Fax: +33 3 8327 8319
Web: http://www.loria.fr/~evincent/