Proposal of a Sound Source Separation Method Using Image Signal Processing of a Spatio-Temporal Sound Pressure Distribution Image

Ozawa K, Ito M, Shimizu G, Morise M, Sakamoto S. Proposal of a Sound Source Separation Method Using Image Signal Processing of a Spatio-Temporal Sound Pressure Distribution Image. In: AES Conference: 2018 AES International Conference on Spatial Reproduction - Aesthetics and Science. Audio Engineering Society; 2018. Paper PP-6. Available from: https://aes.org/publications/elibrary-page/?id=19614

@inproceedings{Ozawa2018_19614,
  author = {Ozawa, Kenji and Ito, Masaaki and Shimizu, Genya and Morise, Masanori and Sakamoto, Shuichi},
  title = {{Proposal of a Sound Source Separation Method Using Image Signal Processing of a Spatio-Temporal Sound Pressure Distribution Image}},
  booktitle = {AES Conference: 2018 AES International Conference on Spatial Reproduction - Aesthetics and Science},
  note = {Paper PP-6},
  year = {2018},
  month = jul,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=19614}
}

TY  - CPAPER
TI  - Proposal of a Sound Source Separation Method Using Image Signal Processing of a Spatio-Temporal Sound Pressure Distribution Image
AU  - Ozawa, Kenji
AU  - Ito, Masaaki
AU  - Shimizu, Genya
AU  - Morise, Masanori
AU  - Sakamoto, Shuichi
T2  - AES Conference: 2018 AES International Conference on Spatial Reproduction - Aesthetics and Science
M1  - Paper PP-6
PY  - 2018
DA  - 2018/07/06
UR  - https://aes.org/publications/elibrary-page/?id=19614
PB  - Audio Engineering Society
LA  - en
AB  - This paper proposes a sound source separation method using image signal processing and a microphone array. First, a spatio-temporal sound pressure distribution (STSPD) image is formed based on microphone outputs. Two-dimensional fast Fourier transform (2D FFT) transforms this image into a spectrum, in which sounds from different directions are separated into the components on different lines naturally. To separate sound sources, every line in the spectrum is extracted and 2D inverse FFT is applied. A method to restore a ?ne STSPD image from the sparse-microphone array is also proposed. Although the basic performance of the proposed method is comparable to a conventional delay and sum array, methods that are more sophisticated can be applied for improved performance.
ER  -