Real-time 2 dimensional sound source localization by 128-channel huge microphone array

Tamai, Y.; Kagami, Satoshi; Mizoguchi, Hiroshi; Amemiya, Y.; Nagashima, Koichi; Takano, Tsuyoshi

doi:10.1109/roman.2004.1374731

Cited by 20 publications

(13 citation statements)

References 5 publications

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“…Such a problem is often mentioned in the literature: in [97], where an array of 128 microphones spreaded into a room is used, the authors proposed to filter out all the frequencies below 500 Hz; the reference [98] gets close conclusions when simulating the 8-microphone antenna implemented on the small mobile platform EvBoy II: while the beampattern main lobe is thin enough for frequencies over 1 kHz, frequencies below 800 Hz cannot be exploited for localization; even with a three-ring 32-microphone array. [99] shows that the bad array directivity at low frequencies and the aliasing effect at low wavelengths conducts the localization to be performed only for frequencies between 1 and 2 kHz.…”

Section: Beamformingmentioning

confidence: 99%

A survey on sound source localization in robotics: From binaural to array processing methods

Argentieri

Danès

Souères

2015

Computer Speech & Language

136

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This paper attempts to provide a state-of-the-art of sound source localization in Robotics. Noticeably, this context raises original constraints-e.g. embeddability, real time, broadband environments, noise and reverberation-which are seldom simultaneously taken into account in Acoustics or Signal Processing. A comprehensive review is proposed of recent robotics achievements, be they binaural or rooted in Array Processing techniques. The connections are highlighted with the underlying theory as well as with elements of physiology and neurology of human hearing.

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Section: Beamformingmentioning

confidence: 99%

A survey on sound source localization in robotics: From binaural to array processing methods

Argentieri

Danès

Souères

2015

Computer Speech & Language

136

View full text Add to dashboard Cite

show abstract

“…Among various kinds of sound source localization methods, generalized cross-correlation (GCC)-based methods (Brandstein and Silverman, 1997;Carter et al, 1973;Knapp and Carter, 1976;Nikas and Shao, 1995) were discussed for robot localization application (Wang et al, 2004). In general, sound-based robot localization system uses a speaker mounted on the robot to produce sound and estimates the location of the sound source, which is the robot's location, by a set of microphone array installed in the room (Tamai et al, 2004a;Wang et al, 2004). The main difficulty for indoor robot localization using sound wave is the complex propagation behavior such as reflection and diffraction.…”

Section: Traditional Sound-based Robot Localization Methods and Knownmentioning

confidence: 99%

“…These sound-related devices can generally provide a more nature way for robots to communicate with human. Additionally, some researchers believe that these devices can be utilized for robot localization (Tamai et al, 2004a;Wang et al, 2004). This work investigates the feasibility of using sound field feature matching for robot's location and orientation detection and proposes a robust soundbased indoor robot's pose detection system utilizing two microphones.…”

Section: Introductionmentioning

confidence: 99%

Indoor sound field feature matching for robot’s location and orientation detection

Liu

Cheng

2008

Pattern Recognition Letters

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“…Huge microphone arrays have been widely researched at Tokyo University of Science (128 ch) [2], the University of Electro-Communication (156 ch) [3], Brown University and Rutgers University (512 ch) [4]- [5], and the Massachusetts Institute of Technology (1,020 ch) [1]. However, obstacles to their practical use persist: increasing computation and power consumption.…”

Section: Introductionmentioning

confidence: 99%

Intelligent ubiquitous sensor network for sound acquisition

Kugata

Takagi

Noguchi

et al. 2010

Proceedings of 2010 IEEE International Symposium on Circuits and Systems

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Abstract-We propose a microphone array network that realizes ubiquitous sound acquisition. Nodes with 16 microphones are connected to form a large sound acquisition system that carries out voice activity detection (VAD), sound source localization and sound source separation. The three operations are distributed among nodes using network. Because the VAD is implemented to manage power consumption, the system consumes little power when speech is not active. The power of the VAD module is only 2.1 mW on an FPGA. The system can improve an SNR by 7.75 dB using 112 microphones.Index Terms-Microphone array, ubiquitous sensing, sensor network, distribution network, low-power system ISCAS Track Selection-Digital Signal Processing INTRODUCTIONIn recent years, information processing technology improvements have realized real-time sound processing systems with microphone arrays. A microphone array can localize sound sources and separate multiple sources using the acquired sounds' spatial information. The computational effort of these operations increases polynomially with the number of microphones, but the performance of these operations is known to improve concomitantly [1]. To reduce the increasing power of a microphone array and to satisfy the recent demand for ubiquitous sound acquisition, it is necessary to realize a low-power, large sound-processing system.Huge microphone arrays have been widely researched at Tokyo University of Science (128 ch To implement a microphone array as an actual ubiquitous sound acquisition system, we propose to divide the huge array into sub-arrays and produce a network: an intelligent ubiquitous sensor network (IUSN). The sub-array nodes can be set up on a room's walls and ceiling. The performance can be improved by increasing the nodes, but the communication between nodes does not increase so much in our system.

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Real-time 2 dimensional sound source localization by 128-channel huge microphone array

Cited by 20 publications

References 5 publications

A survey on sound source localization in robotics: From binaural to array processing methods

A survey on sound source localization in robotics: From binaural to array processing methods

Indoor sound field feature matching for robot’s location and orientation detection

Intelligent ubiquitous sensor network for sound acquisition

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