In this paper, the direction of arrival (DOA) estimation of multiple speech sources in reverberant environments is investigated based on the recording of a soundfield microphone. First, the recordings are analyzed in the time-frequency (T-F) domain to detect both “points” (single T-F points) and “regions” (multiple, adjacent T-F points) corresponding to a single source with low reverberation (known as low-reverberant-single-source (LRSS) points). Then, a LRSS point detection algorithm is proposed based on a joint dominance measure and instantaneous single-source point (SSP) identification. Following this, initial DOA estimates obtained for the detected LRSS points are analyzed using a Gaussian Mixture Model (GMM) derived by the Expectation-Maximization (EM) algorithm to cluster components into sources or outliers using a rule-based method. Finally, the DOA of each actual source is obtained from the estimated source components. Experiments on both simulated data and data recorded in an actual acoustic chamber demonstrate that the proposed algorithm exhibits improved performance for the DOA estimation in reverberant environments when compared to several existing approaches.

Preserving audio scenes in the form of audio objects has become common in recent years. Object-based audio techniques provide more flexibility for personalized rendering as well as a more accurate audio object trajectory. For encoding and transmitting multiple audio objects in a lossy manner, a new compression framework for multiple simultaneously occurring audio objects is presented in this work. The proposed encoding approach is based on the intra-object sparsity (approximate k-sparsity). After establishing a quantitative measure of approximate k-sparsity, statistical analysis is employed to validate the proposed intra-object sparsity of audio objects. By exploring this intra-object sparsity, multiple simultaneously occurring audio objects are compressed into a mono downmix signal with side information. This downmix signal can be further compressed by legacy audio codecs. Meanwhile, the side information is transmitted in a lossless manner. The objective and subjective evaluations revealed that the proposed compression framework achieved better perceptual quality compared to an existing technique where up to eight audio objects are considered. The subjective evaluations also confirmed that the proposed approach is able to achieve scalable transmission according to the bandwidth while preserving the perceptual quality of both the individual audio objects and the spatial audio scenes.

This paper proposes a method to design a planar first-order loudspeaker array structure for global active noise control. Compared with the traditional spherical loudspeaker array, the planar array provides a practical design with flexible source locations. The planar array is capable of achieving global noise control, provided that the loudspeakers have general variable first-order responses in elevation. On x-y plane, we use spherical harmonics to analyze the required first-order loudspeakers consisting of monopole and tangential dipole components. By exploiting the properties of the associated Legendre functions and its derivative, we can divide the primary soundfield into even harmonics controlled by the monopole component, and odd harmonics controlled by the dipole component. Through the appropriate choice of radii of circles, we avoid the ill-conditioning problem of matrix inversion and derive a robust solution for loudspeaker weights to suppress the primary noise field. Besides, we use the closely-located monopole pairs, instead of the ideal general first-order loudspeakers, to design an alternative planar array for practical implementation. As an illustration, we use several simulation examples to validate the performance of the two proposed planar loudspeaker arrays.