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2-year positions on distant-mic ASR
Dear list,
We are offering two positions on distant-mic ASR in the context of a
large-scale R&D project on voice control of home appliances involving 5
companies and 3 academic labs.
Successful candidates will perform research on state-of-the-art acoustic
models and contribute to transfer their ideas into a commercial ASR product.
* Research engineer (ideal start: Jan/Feb 2015 - duration: 2 years)
- collaborate with a speech company on the DNN acoustic model setup
- assess various multicondition training and speaker adaptation
strategies for reverberant and noisy speech
- design improved confidence measures
* Postdoc (ideal start: Apr 2015 - duration: 2 years)
- explore adaptation of DNNs to the reverberation conditions
- explore adaptation of DNNs to noise by uncertainty propagation
- design improved uncertainty estimators
Salary: 2600 to 3300 €/month gross depending on experience, plus free
health insurance and additional benefits
Ideal profile:
- PhD on speech processing, machine learning, audio signal processing,
or applied statistics
- proficient programming in C++, shell, Matlab/Python
- optional experience with Kaldi or another ASR 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 Dec 12. Please
apply as soon as possible before that date.
References:
[1] M. Ravanelli, M. Omologo, "On the selection of the impulse responses
for distant-speech recognition based on contaminated speech training",
in Proc. Interspeech, 2014.
[2] B. Dumortier, E. Vincent, "Blind RT60 estimation robust across room
sizes and source distances", in Proc. ICASSP, 2014.
[3] M.L. Seltzer, D. Yu, Y. Wang, "An investigation of noise robustness
of deep neural networks," in Proc. ICASSP, 2013.
[4] B. Li, K.C. Sim, "An ideal hidden-activation mask for deep neural
networks based noise-robust speech recognition," in Proc. ICASSP, 2014.
[5] D.T. Tran, E. Vincent, D. Jouvet, “Fusion of multiple uncertainty
estimators and propagators for noise robust ASR”, in Proc. ICASSP, 2014.
--
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/