2006Unpublished venueRequires access

Robust Tracking of Multiple Sound Sources by Spatial Integration of Room And Robot Microphone Arrays

Kazuhiro Nakadai, Hironori Nakajima, Mai Murase, S. Kaijiri, Kodai Yamada, Toshiya Nakamura, Y. Hasegawa, Hiroshi G. Okuno, Hiroshi Tsujino

Open publisher page 47 citations

Abstract

Sound source tracking is an important function for a robot operating in a daily environment, because the robot should recognize where a sound event such as speech, music and other environmental sounds originates from. This paper addresses sound source tracking by integrating a room and a robot microphone array. The room microphone array consists of 64 microphones attached to the walls. It provides 2D (x-y) sound source localization based on a weighted delay-and-sum beamforming method. The robot microphone array consists of eight microphones installed on a robot head, and localizes multiple sound sources in azimuth. The localization results are integrated to track sound sources by using a particle filter for multiple sound sources. The experimental results show that particle filter based integration reduces localization errors and provides accurate and robust 2D sound source tracking.

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What this paper is about

Sound source tracking is an important function for a robot operating in a daily environment, because the robot should recognize where a sound event such as speech, music and other environmental sounds originates from. This paper addresses sound source tracking by integrating a room and a robot microphone array. The room microphone array consists of 64 microphones attached to the walls. It provides 2D (x-y) sound source localization based on a weighted delay-and-sum beamforming method. The robot microphone array consists of eight microphones installed on a robot head, and localizes multiple sound sources in azimuth. The localization results are integrated to track sound sources by using a particle filter for multiple sound sources. The experimental results show that particle filter based integration reduces localization errors and provides accurate and robust 2D sound source tracking.

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Available abstract

Sound source tracking is an important function for a robot operating in a daily environment, because the robot should recognize where a sound event such as speech, music and other environmental sounds originates from. This paper addresses sound source tracking by integrating a room and a robot microphone array. The room microphone array consists of 64 microphones attached to the walls. It provides 2D (x-y) sound source localization based on a weighted delay-and-sum beamforming method. The robot microphone array consists of eight microphones installed on a robot head, and localizes multiple sound sources in azimuth. The localization results are integrated to track sound sources by using a particle filter for multiple sound sources. The experimental results show that particle filter based integration reduces localization errors and provides accurate and robust 2D sound source tracking.

Key concepts: Microphone array, Acoustic source localization, Noise-canceling microphone, Beamforming, Microphone, Computer science, Acoustics, Robot

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