NIPS 2008 WORKSHOP on Speech and Language: Learning-based Methods and Systems


Speech and Language: Learning-based Methods and Systems

Friday, December 12, 2008

Whistler, British Columbia, Canada



This workshop is intended for researchers interested in machine learning methods for speech and language processing and in unifying approaches to several outstanding speech and language processing issues.

In the last few years, significant progress has been made in both research and commercial applications of speech and language processing. Despite the superior empirical results, however, there remain important theoretical issues to be addressed. Theoretical advancement is expected to drive greater system performance improvement, which in turn generates the new need of in-depth studies of emerging novel learning and modeling methodologies. The main goal of this workshop is to fill in the above need, with the main focus on the fundamental issues of new emerging approaches and empirical applications in speech and language processing. Another focus of this workshop is on the unification of learning approaches to speech and language processing problems. Many problems in speech processing and in language processing share a wide range of similarities (despite conspicuous differences), and techniques in speech and language processing fields can be successfully cross-fertilized. It is of great interest to study unifying modeling and learning approaches across these two fields.

In summary, we hope that this workshop will present an opportunity for intensive discussions of emerging learning methods among speech processing, language processing, and machine learning researchers, and will inspire unifying approaches to problems across the speech and language processing fields.

The workshop will feature world-class speakers, paper session, and lively discussions. We expect but not limited to the following topics in the workshop:

? Discriminative training of statistical classifiers

? Unsupervised/semi-supervised learning algorithms for sequential pattern recognition

? Model adaptation to new/diverse conditions

? Multi-engine approaches for sequential pattern recognition

? Unifying approaches to speech processing and language processing


At this workshop, we expect to touch on broad aspects of machine learning technology for speech and language processing. We have invited eight prominent researchers to give invited talks, each of which will cover a specific topic in-depth, and in overall we hope to present a balanced view on this theme to the audience.

1.�������� Geoffrey Hinton, University of Toronto

New Multi-level Models for High-dimensional Sequential Data


2.�������� Ralf Schl�ter, RWTH Aachen University

Log-linear Approach to Discriminative Training


3.�������� Mari Ostendorf, University of Washington

On the Role of Local Learning for Language Modeling


4.�������� Yunxin Zhao, University of Missouri

Ensemble Machine Learning Methods for Acoustic Modeling of Speech


5.�������� Jeff Bilmes, University of Washington

Relations Between Graph Triangulation, Stack Decoding, and Synchronous Decoding


6.�������� Pedro Domingos, University of Washington

Markov Logic Networks: A Unified Approach to Language Processing


7.�������� Robert Moore, Microsoft Research

Some Machine Learning Issues in Discriminative Bilingual Word Alignment


8.�������� Andreas Stolcke, SRI international

Machine Learning for Speaker Recognition



Friday, Dec. 12, 2008

?7:30 ?8:10���� Invited talk by Geoffrey Hinton

?8:10 ?8:50���� Invited talk by Ralf Schl�ter

?8:50 ?9:20���� Poster Session and Break

?/span>9:20??/span> 10:00�� Invited talk by Mari Ostendorf

10:00 ?10:40��?Invited talk by Yunxin Zhao


10:40 ?15:30��? Lunch Break and Poster


15:30 ?16:10��?Invited talk by Jeff Bilmes

16:10 ?16:50��?Invited talk by Pedro Domingos

16:50 ?17:05��? Coffee break

17:05 ?17:45��?Invited talk by Robert Moore

17:45 ?18:25��?Invited talk by Andreas Stolcke

18:25 ?18:30��?Conclusion and Close



Paper submission is closed!



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Xiaodong He

Affiliation:  Natural Language Processing Group, Microsoft Research,

Address:   One Microsoft Way, Redmond, WA 98052, USA




Li Deng

Affiliation:  Speech Research Group, Microsoft Research,

Address:   One Microsoft Way, Redmond, WA 98052, USA




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