Speaker diarization system for RT07 and RT09 meeting room audio

This paper describes an improved speaker diarization system for the Single Distant Microphone (SDM) task in the 2007 and 2009 NIST Rich Transcription Meeting Recognition Evaluations. The system includes three main modules: front-end processing, initial speaker clustering and cluster purification/merging. The front-end processing involves the Wiener filtering for the targeted audio channels and a self-adaptation speech activity detection algorithm. A simple but effective energy based segmentation is applied to chunk the meeting data into small segments to construct the initial clusters. An enhanced purification algorithm is proposed to further improve the performance after the preliminary purification, and the BIC criterion is adopted for the cluster merging. The system achieves competitive overall DERs of 15.67% for RT07 SDM speaker diarization task and 17.34% for RT09 SDM speaker diarization task.