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Sparse sound field decomposition for super-resolution in recording and reproduction
Author(s) -
Shoichi Koyama,
Naoki Murata,
Hiroshi Saruwatari
Publication year - 2018
Publication title -
the journal of the acoustical society of america
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.619
H-Index - 187
eISSN - 1520-8524
pISSN - 0001-4966
DOI - 10.1121/1.5042215
Subject(s) - acoustics , aliasing , field (mathematics) , microphone array , computer science , microphone , sound pressure , mathematics , physics , artificial intelligence , undersampling , pure mathematics
A sound field recording and reproduction method based on sparse sound field decomposition is proposed. Most current methods are based on plane-wave or harmonic decomposition of the pressure distribution obtained by microphones, which leads to spatial aliasing artifacts with severe effects. This paper proposes a method for sound field decomposition based on a generative model of the sound field consisting of near-field source components and far-field plane-wave components. Since the distribution of the near-field source components can be assumed to be spatially sparse, the pressure distribution obtained by the microphones can be decomposed into these two components using sparse decomposition algorithms. Using the proposed method, the sound field can be more accurately interpolated and super-resolution in recording and reproduction can be achieved. Experimental results show that the reproduction accuracy above the spatial Nyquist frequency determined by the microphone intervals was improved compared with that of the current methods.

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