Sound Source Localization Using Joint Bayesian Estimation With a Hierarchical Noise Model

Abstract

The performance of sound source localization is often reduced by the presence of colored noise in the environment, such as room reverberation. In this study, a method for estimating the noise spatial covariance using a hierarchical model is proposed and its performance is evaluated. By employing the hierarchical model in joint Bayesian estimation, robust estimation of the covariance is expected with a relatively small amount of data. Moreover, a method of jointly estimating the number of sources is introduced so that it can be used for cases in which the number of active sources dynamically changes, for example, speech signals. The results of the experiments performed using actual room reverberation show the effectiveness of the proposed method.