Identification of the Room Characteristics Using a Spherical Microphone Array
* Presenting author
Microphone arrays have been used in the last decades to identify sound sources in several environments. One of the most used techniques is the beamforming, that can be understood as a spatial filter for selecting sound waves coming from the direction of interest. Nowadays, due the acquisition hardware and the processing software capacity, it is already possible apply the beamforming using high numbers of microphone in the array. This condition allows, for example, use a spherical microphone array (SMA) for monitoring all directions in space with high resolution. This research proposes to use a SMA aiming not only identify sound sources, but also the characteristics of the environment, such as dimensions, baffles positions, specular reflection coefficients and others. This will be possible with a rotating microphone array that provides 98 measure points in a virtual spherical surface. The processing that will be adopted consist in applying the spherical harmonic decomposition in the sound field around the spherical surface created by a known sound source and using the Wavelet Transform to identify the directions and time of arrival of the direct sound and the reflections. It will be presented simulations and measurements in a real environment.