Reverberation-Robust Self-Calibration and Synchronization of Distributed Microphone Arrays by Mitigating Heteroscedasticity and Outlier Occurrence in TDoA Measurements.

The network of distributed microphone arrays is usually established in an ad hoc manner; hence, network parameters such as the mutual positioning and rotation of the arrays, positions of sources, and synchronization of their recording onset times are initially unknown. In this article, we consider the problem of passively jointly self-calibrating and synchronizing distributed arrays in reverberant rooms. We use a typical two-step approach where, initially, the relative geometry of the network is estimated using Direction of Arrival (DoA) measurements. Subsequently, the absolute scale and synchronization parameters are estimated using Time Difference of Arrival (TDoA) measurements. This article presents methods to improve the robustness and accuracy of estimation of the absolute geometric scaling and synchronization parameters in reverberant conditions, in which TDoA measurements do not follow a normal distribution; furthermore, outliers often occur. To remedy these issues, we propose a Weighted Least Squares (WLS) estimator and schema for weighting the TDoA measurements to increase the estimation accuracy from heteroscedastic TDoA measurements. In addition, we propose an iterative reweighing algorithm with a binary weight to detect and reject TDoA outliers, which exploits the residuals of the parametric model in the least absolute value minimization. A numerical evaluation shows significant improvements in the proposed method over the state of the art in terms of the relative scaling error and mean absolute value of the synchronization parameters.

Raking early reflection signals for late reverberation and noise reduction.

In acoustic environments the microphones capture a source signal corrupted by room reverberation and noise. This letter presents two optimum spatial filters which jointly reduce late reverberation and noise for the sound source recorded from distance in a reverberant room. The proposed rake filters are derived by incorporating spatial information about early reflection paths into the multichannel filter design. The results of performed numerical and real experiments indicate that the proposed rake filtering improves the reduction of detrimental late reverberation and noise, and increases the perceptual quality of the recorded speech.

Mixing time prediction using spherical microphone arrays.

Human perception of room acoustics depends among others on the time of transition from early reflections to late reverberation in room impulse responses, which is known as mixing time. In this letter, a multi-channel mixing time prediction method is proposed, which in contrast to state-of-the-art channel-based predictors accounts for spatiotemporal properties of the sound field. The proposed diffuseness-based method is compared with existing model- and channel-based prediction methods through measurements and acoustic simulations, and is shown to correlate well with the perceptual mixing time. Furthermore, insights into relations between prediction methods and mixing time definitions based on reflection density are presented.

Room geometry inference based on spherical microphone array eigenbeam processing.

The knowledge of parameters characterizing an acoustic environment, such as the geometric information about a room, can be used to enhance the performance of several audio applications. In this paper, a novel method for three-dimensional room geometry inference based on robust and high-resolution beamforming techniques for spherical microphone arrays is presented. Unlike other approaches that are based on the measurement and processing of multiple room impulse responses, here, microphone array signal processing techniques for uncontrolled broadband acoustic signals are applied. First, the directions of arrival (DOAs) and time differences of arrival (TDOAs) of the direct signal and room reflections are estimated using high-resolution robust broadband beamforming techniques and cross-correlation analysis. In this context, the main challenges include the low reflected-signal to background-noise power ratio, the low energy of reflected signals relative to the direct signal, and their strong correlation with the direct signal and among each other. Second, the DOA and TDOA information is combined to infer the room geometry using geometric relations. The high accuracy of the proposed room geometry inference technique is confirmed by experimental evaluations based on both simulated and measured data for moderately reverberant rooms.

Localization of distinct reflections in rooms using spherical microphone array eigenbeam processing.

This paper presents an experimental and comparative study of several spherical microphone array eigenbeam (EB) processing techniques for localization of early reflections in room acoustic environments, which is a relevant research topic in both audio signal processing and room acoustics. This paper focuses on steered beamformer-based and subspace-based localization techniques implemented in the spherical EB domain, including the plane-wave decomposition, eigenbeam delay and sum, eigenbeam minimum variance distortionless response, eigenbeam multiple signal classification (EB-MUSIC), and eigenbeam estimation of signal parameters via rotational invariance techniques (EB-ESPRIT) methods. The directions of arrival of the original sound source and the associated reflection signals in acoustic environments are estimated from acoustic maps of the rooms, which are obtained using a spherical microphone array. The EB-domain-based frequency smoothing and white noise gain control techniques are derived and employed to improve the performance and robustness of reflection localization. The applicability of the presented methods in practice is confirmed by experiments carried out in real rooms.