DocumentCode :
1822426
Title :
Low-Traffic and Low-Power Data-Intensive Sound Acquisition with Perfect Aggregation Specialized for Microphone Array Networks
Author :
Noguchi, Hiroki ; Takagi, Tomoya ; Kugata, Koji ; Yoshimoto, Masahiko ; Kawaguchi, Hiroshi
Author_Institution :
Dept. of Comput. & Syst. Eng., Kobe Univ., Kobe, Japan
fYear :
2010
fDate :
18-25 July 2010
Firstpage :
157
Lastpage :
162
Abstract :
We propose a microphone array network that realizes ubiquitous sound acquisition. Several nodes with 16 microphones are connected to form a novel huge sound acquisition system, which carries out voice activity detection (VAD), sound source localization, and separation. The three operations are distributed among nodes. Using the distributed network, we achieve a low-traffic data-intensive array network. To manage nodes´ power consumption, VAD is implemented. Consequently, the system uses little power when speech is not active. For sound localization, a network-connected multiple signal classification (MUSIC) algorithm is used. The sound separation system can improve a signal-noise ratio (SNR) by 7.75 dB using 112 microphones. Network traffic is reduced by 99.11% when using 1024 microphones.
Keywords :
acoustic signal detection; microphone arrays; signal classification; MUSIC algorithm; SNR; VAD; data intensive sound acquisition system; distributed network; microphone array networks; network traffic; network-connected multiple signal classification algorithm; nodes power consumption; signal-noise ratio; sound source localization; sound source separation; voice activity detection; Accuracy; Arrays; Microphones; Multiple signal classification; Signal to noise ratio; Speech; Synchronization; low-power system; microphone array; perfect aggregation; sensor network; ubiquitous sensing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Sensor Technologies and Applications (SENSORCOMM), 2010 Fourth International Conference on
Conference_Location :
Venice
Print_ISBN :
978-1-4244-7538-4
Type :
conf
DOI :
10.1109/SENSORCOMM.2010.32
Filename :
5558069
Link To Document :
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