Voice activity detection (VAD) is a critical component in various applications, such as voice recognition, speaker identification, and hands-free communication systems. With the increasing demand for personalized and context-aware technologies, the need for customized and effective VAD systems has become paramount. In this article, we present a comparative analysis of Personalized Voice Activity Detection (PVAD) systems to evaluate their real-world effectiveness. We present a comprehensive approach to evaluating PVAD systems, incorporating several performance metrics, such as frame- and expression-level error rates and onset detection latency, along with user-level analysis. Through extensive experimentation and evaluation, we provide a deep understanding of the strengths and limitations of various PVAD variants. This article advances the understanding of PVAD technology by providing insights into its effectiveness and feasibility in practical applications using a comprehensive set of metrics.
