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Deep Learning Workshop 2013 : ICML 2013 Workshop on Deep Learning for Audio, Speech, and Language Processing

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Link: https://sites.google.com/site/deeplearningicml2013/
 
When Jun 16, 2013 - Jun 16, 2013
Where Atlanta
Submission Deadline Mar 30, 2013
Notification Due Apr 30, 2013
Final Version Due May 15, 2013
Categories    machine learning   deep learning
 

Call For Papers

Deep learning techniques have enjoyed enormous success in the speech and language processing community over the past few years, beating previous state-of-the-art approaches to acoustic modeling, language modeling, and natural language processing. The focus of this workshop will be on deep learning approaches to problems in audio, speech, and language. Talks and papers on new models and learning algorithms that can address some of the challenges of these tasks, such as their inherent temporal structure or the need to handle very large data sets, but that have not yet been applied to audio, speech, or language, are encouraged. This goal of this workshop is to provide a uniquely focused forum for the discussion of the intersection of fields of deep learning and audio, speech, and language, bringing together researchers to investigate some of these novel deep learning techniques, and discuss how they can be incorporated into audio, speech, and language processing. This one-day workshop will include a mixture of invited talks, contributed talks, and poster sessions. One goal in selecting both invited and contributed talks will be to cover a broad range of subjects pertinent to the workshop theme, because we believe that an important role of these workshops is the promotion of cross-pollination between fields. The deadline for paper submissions will be March 30, 2013.

Please visit the following website for more information: https://sites.google.com/site/deeplearningicml2013/
Submission deadline: March 30, 2013
Acceptance notification: April 30, 2103
Final paper submission: May 15, 2013
Workshop date: June 16, 2013
Organizers: Brian Kingsbury, IBM, Tara Sainath, IBM, Li Deng, Microsoft, Andrew Senior, Google

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