Source-specific system identification

Many applications in audio communication require the identification of Loudspeaker-Enclosure-Microphone Systems (LEMS) with multiple inputs and outputs. The according computational complexity typically grows at least proportionally along the number of acoustic paths, which is the product of the number of loudspeakers and the number of microphones. Furthermore, the typical, highly correlated loudspeaker signals preclude an exact identification of the LEMS. To this end, a novel system identification scheme employing prior information from an object-based rendering system, e.g., Ambisonics [1,2] or Wave Field Synthesis (WFS) [3,4], is proposed. In this scheme, only a source-specific system from each virtual source to each microphone is identified adaptively and uniquely. This estimate for a source-specific system can then be transformed into a statistically optimal estimate of the LEMS, which could have been found by a computationally expensive direct LEMS estimation as well. The basic concept is extended to time-varying acoustic scenes and simulations of a WFS application confirm the validity of this novel approach for system identification.