I. Introduction
Diarization systems for speakers encompass the task of labeling audio or video recordings with tags that indicate the identities of the speakers. [1]. It needs to make decisions on corresponding small segments varying from a few second to several segments [2]. By identifying speaker-specific events and partitioning audio streams accordingly, speaker diarization proves to be a valuable tool across numerous language-related applications, including but not limited to information retrieval from broadcast news and telephone conversations, speaker indexing and retrieval, speech recognition integrated with speaker identification, as well as diarizing meetings and lectures.