Online Speaker Diarization with a Size-Monitored Growing Neural Gas Algorithm
Abstract
This paper proposes a method for segmenting and clustering an audio flow on the basis of speaker turns. This process, also known as speaker diarization, is of major importance in multimedia indexation. Here, we propose to realize this process online and without any prior knowledge on the number of speakers. This is done thanks to a statistical modelling of speakers based on a size-monitored growing neural gas algorithm.