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Author:

Pan, Jian-hong (Pan, Jian-hong.) | Bao, Chang-chun (Bao, Chang-chun.) (Scholars:鲍长春) | Bu, Bing (Bu, Bing.) | Jia, Mao-shen (Jia, Mao-shen.)

Indexed by:

CPCI-S

Abstract:

We present a new method for spatial soundfield recording based on the application of compressed sensing theory. The major problem in spatial soundfield recording system is how to record the higher order harmonic components of a given soundfield using as few as possible of microphones. The proposed method is under the assumption that the soundfield is sparse in source domain. More specifically, based on the general model of soundfield, we apply sparse decomposition to the harmonics, which are calculated according to the sound pressure received by a circular microphone array, and then upscale the harmonics to higher order. Simulation results indicate that our proposed method can drastically reduce the required number of microphones for capturing large region soundfield compared to the current methods, especially in high frequencies.

Keyword:

large region higher order harmonics Spatial soundfield recording compressed sensing

Author Community:

  • [ 1 ] [Pan, Jian-hong]Beijing Univ Technol, Sch Elect Informat & Control Engn, Speech & Audio Signal Proc Lab, Beijing 100124, Peoples R China
  • [ 2 ] [Bao, Chang-chun]Beijing Univ Technol, Sch Elect Informat & Control Engn, Speech & Audio Signal Proc Lab, Beijing 100124, Peoples R China
  • [ 3 ] [Bu, Bing]Beijing Univ Technol, Sch Elect Informat & Control Engn, Speech & Audio Signal Proc Lab, Beijing 100124, Peoples R China
  • [ 4 ] [Jia, Mao-shen]Beijing Univ Technol, Sch Elect Informat & Control Engn, Speech & Audio Signal Proc Lab, Beijing 100124, Peoples R China

Reprint Author's Address:

  • [Pan, Jian-hong]Beijing Univ Technol, Sch Elect Informat & Control Engn, Speech & Audio Signal Proc Lab, Beijing 100124, Peoples R China

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Source :

PROCEEDINGS OF 2016 INTERNATIONAL CONFERENCE ON AUDIO, LANGUAGE AND IMAGE PROCESSING (ICALIP)

Year: 2016

Page: 57-61

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 10

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