  Speaker localization in a reverberant environment is a fundamental problem in
audio signal processing. Many solutions have been developed to tackle this
problem. However, previous algorithms typically assume a stationary environment
in which both the microphone array and the sound sources are not moving. With
the emergence of wearable microphone arrays, acoustic scenes have become
dynamic with moving sources and arrays. This calls for algorithms that perform
well in dynamic environments. In this article, we study the performance of a
speaker localization algorithm in such an environment. The study is based on
the recently published EasyCom speech dataset recorded in reverberant and noisy
environments using a wearable array on glasses. Although the localization
algorithm performs well in static environments, its performance degraded
substantially when used on the EasyCom dataset. The paper presents performance
analysis and proposes methods for improvement.
