Abstract:
This paper studies the direction of arrival estimation of reflections in short time windows of room impulse responses measured with a spherical microphone array. Spectral...Show MoreMetadata
Abstract:
This paper studies the direction of arrival estimation of reflections in short time windows of room impulse responses measured with a spherical microphone array. Spectral-based methods, such as multiple signal classification (MUSIC) and beamforming, are commonly used in the analysis of spatial room impulse responses. However, the room acoustic reflections are highly correlated or even coherent in a single analysis window and this imposes limitations on the use of spectral-based methods. Here, we apply maximum likelihood (ML) methods, which are suitable for direction of arrival estimation of coherent reflections. These methods have been earlier developed in the linear space domain and here we present the ML methods in the context of spherical microphone array processing and room impulse responses. Experiments are conducted with simulated and real data using the em32 Eigenmike. The results show that direction estimation with ML methods is more robust against noise and less biased than MUSIC or beamforming.
Published in: IEEE/ACM Transactions on Audio, Speech, and Language Processing ( Volume: 23, Issue: 10, October 2015)