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Computer Engineering - Bachelor\'s Degree2005 - 2009 (4 years)
Computer Engineering - Master Degree2012 - 2013 (1 year)
Sound source identification for scene analysis
The ability to recognize objects and events by interpreting sound signals is one of the fundamental qualities of human. The ability to categorize objects and events using auditory signals is extremely important, but it is a difficult task in robots. In this paper, different supervised learning methods using distinctive features from sound data were compared as part of a system for robots to clasify objects and events automatically using auditory features of environmental sound.
Scene analysis through auditory event monitoring
In this paper, we propose auditory scene analysis methods for robots in order to monitor events to detect failures and learn from their experiences. Audio data are convenient for these purposes to detect environmental changes surrounding a robot and especially complement visual data. In our study, we investigate supervised learning methods using informative features from sound data for efficient categorization in manipulation scenarios.
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