Comparison of diarization tools for building speaker database

Abstract

This paper compares open source diarization toolkits (LIUM, DiarTK, ALIZE-Lia_Ral), which were designed for extraction of speaker identity from audio records without any prior information about the analysed data. The comparative study of used diarization tools was performed for three different types of analysed data (broadcast news - BN and TV shows). Corresponding values of achieved DER measure are presented here. The automatic speaker diarization system developed by LIUM was able to identified speech segments belonging to speakers at very good level. Its segmentation outputs can be used to build a speaker database.