Original papers: Real-time recognition of sick pig cough sounds
Computers and Electronics in Agriculture
Daily sound recognition using pitch-cluster-maps for mobile robot audition
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Self-organization of behavioral primitives as multiple attractor dynamics: A robot experiment
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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Our goal is to develop a system that is able to learn and classify environmental sounds for robots working in the real world. In the real world, two main restrictions pertain in learning. First, the system has to learn using only a small amount of data in a limited time because of hardware restrictions. Second, it has to adapt to unknown data since it is virtually impossible to collect samples of all environmental sounds. We used a neuro-dynamical model to build a prediction and classification system which can self-organize sound classes into parameters by learning samples. The proposed system searches space of parameters for classifying. In the experiment, we evaluated the accuracy of classification for known and unknown sound classes.