Statistical physics, machine learning, andits application to speech and pattern recognition
October 12, 2016 - October 15, 2016 |
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Dates : October 12 - October, 15, 2016
Place : Incheon (Nest Hotel)
Machine Learning is the study of finding structure in complex data, and it can exploits the recovered data structure for different tasks. Speech Processing and Pattern Recognition provide data with intricate complexity and a multitude of different tasks including:
signal enhancement, signal separation, compression, or classification. The combination of speech processing research with Machine Learning methods has consequently emerged as a very active and important research field.
The international symposium on "Machine Learning and Its Applications to Speech and Pattern Recognition" brings together a broad range of researchers from Machine Learning and from the fields of speech and acoustic data processing. The symposium is organized as a medium to exchange recent research results and to discuss possible Machine Learning solutions to current and future challenges of acoustic data processing and pattern recognition. We cover basic research questions and a broad range of data driven approaches for speech and acoustic data processing and pattern recognition, where Machine Learning methods are applied to solve concrete tasks.
Presentations of researchers, ample discussion time, and social events will provide an environment with strong focus on
interdisciplinary and interactivity for intensive scientific interaction and international research community building.
TOPICS :
Machine learning technology
Acoustic processing in human and machine
Feature selection, feature learning, and comparison
Applications and technical solutions for limited source
Statistical physics of machine learning
Speakers :
Kang-Hun Ahn (Chungnam National University)
Junghyo Jo (APCTP/POSTECH)
Kyung Myun Lee (KAIST)
Minho Lee (Kyungpook National University)
Soo-Young Lee(KAIST)
Jörg Lücke (Oldenburg University)
Yung-Kyun Noh (Seoul National University)
Steven van der Par (Oldenburg University)
Joachim Thiemann (Oldenburg University)
Makoto Yamada(Kyoto University)
Contact
Ms. Hyemi Kim
Tel : +82-2-958-2638
Emai l: hmkim@kias.re.kr
Supported by
Research Station of KIAS