Daily sound recognition using Pitch-Cluster-Maps for mobile robot audition
Yoko Sasaki, Masahito Kaneyoshi, Satoshi Kagami, Hiroshi Mizoguchi, Tadashi Enomoto · 2009
This paper proposes a sound identification method for a mobile robot in home and office environment. We propose a simple sound database called Pitch-Cluster-Maps(PCMs) based on Vector Quantization approach. Binarized frequency spectrum is used for PCMs codebook generation. It can describe a variety of sound sources, not only voice, from short term sound input. The proposed PCMs sound identification requires several tens(msec) of sound input, and is suitable for a mobile robot application which condition is dynamically changing. We implemented the proposed method on our mobile robot audition system equipped with a 32ch microphone array. Robot noise reduction using proposed PCMs recognition is applied to each input signal of a microphone array. The performance of daily sound recognition for separated sound sources from robot in motion is evaluated.