Blind Localization of Early Room Reflections with Arbitrary Microphone Array

Abstract

Blindly estimating the direction of arrival (DoA) of early room reflections without prior knowledge of the room impulse response or source signal is highly valuable in audio signal processing applications. The FF-PHALCOR (Frequency Focusing PHase ALigned CORrelation) method was recently developed for this purpose, extending the original PHALCOR method to work with arbitrary arrays rather than just spherical ones. Previous studies have provided only initial insights into its performance. This study offers a comprehensive analysis of the method's performance and limitations, examining how reflection characteristics such as delay, amplitude, and spatial density affect its effectiveness. The research also proposes improvements to overcome these limitations, enhancing detection quality and reducing false alarms. Additionally, the study examined how spatial perception is affected by generating room impulse responses using estimated reflection information. The findings suggest a perceptual advantage of the proposed approach over the baseline, with particularly high perceptual quality when using the spherical array with 32 microphones. However, the quality is somewhat reduced when using a semi-circular array with only 6 microphones.

Figures (8)

• Figure 1: Block diagram of the algorithm
• Figure 2: (a) Mean probability of Detection $P_D$ and (b) Mean probability of False Alarms $P_{FA}$, across simulations, as a function of the number of reflections in the ground truth within the first $20\,$ms. The X-axis indicates the count of reflections in $5$ groups, and the Y-axis shows the values of (a) $P_D$ and (b) $P_{FA}$. The outcomes for the semi-circular and em32 arrays are illustrated by the orange and blue lines, respectively.
• Figure 3: (a) The probability of misses ($P_M$) and the count of reflections across varying ranges of reflections amplitudes, and (b) Similar to (a), with reflection delay replacing amplitude.
• Figure 4: The graph shows false alarms plotted against the corresponding delay of the estimates. The blue line represents the count of reflections at various delay intervals.
• Figure 5: Misses resulting from the clustering of multiple reflections into a single cluster. The blue line indicates the total misses, categorized by the range of the number of reflections shown on the X-axis. The orange line illustrates the proportion of these misses as a percentage of the overall misses.