A Spherical Microphone Array for Synthesizing Virtual Directive Microphones in Live Broadcasting and in Post Production

Farina A, Capra A, Chiesi L, Scopece L. A Spherical Microphone Array for Synthesizing Virtual Directive Microphones in Live Broadcasting and in Post Production. In: AES Conference: 40th International Conference: Spatial Audio: Sense the Sound of Space. Audio Engineering Society; 2010. Paper 3-1. Available from: https://aes.org/publications/elibrary-page/?id=15577

@inproceedings{Farina2010_15577,
  author = {Farina, Angelo and Capra, Andrea and Chiesi, Lorenzo and Scopece, Leonardo},
  title = {{A Spherical Microphone Array for Synthesizing Virtual Directive Microphones in Live Broadcasting and in Post Production}},
  booktitle = {AES Conference: 40th International Conference: Spatial Audio: Sense the Sound of Space},
  note = {Paper 3-1},
  year = {2010},
  month = oct,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=15577}
}

TY  - CPAPER
TI  - A Spherical Microphone Array for Synthesizing Virtual Directive Microphones in Live Broadcasting and in Post Production
AU  - Farina, Angelo
AU  - Capra, Andrea
AU  - Chiesi, Lorenzo
AU  - Scopece, Leonardo
T2  - AES Conference: 40th International Conference: Spatial Audio: Sense the Sound of Space
M1  - Paper 3-1
PY  - 2010
DA  - 2010/10/06
UR  - https://aes.org/publications/elibrary-page/?id=15577
PB  - Audio Engineering Society
LA  - en
AB  - The paper describes the theory and the first operational results of a new multichannel recording system based on a 32-capsules spherical microphone array. Up to 7 virtual microphones can be synthesized in real-time, choosing dynamically the directivity pattern (from standard cardioid to 6th-order ultradirective) and the aiming. A graphical user’s interface allows for moving the virtual microphones over a 360-degrees video image. The system employs a novel mathematical theory for computing the matrix of massive FIR filters, which are convolved in real time and with small latency thanks to a partitioned convolution processor.
ER  -