This paper presents speaker diarization system on NIST Rich Transcription 2009 (RT-09) Meeting Recognition evaluation data set for the task of Single Distant Microphone (SDM). A two-step speaker clustering method is proposed. The first step is speaker cluster initialization using speech segments of meeting audio, where we randomly pick a small subset of speech segments and merge them iteratively into a number of clusters. And, the second step is cluster purification, where we introduce a consensus-based speaker segment selection method for efficient speaker cluster modeling that purifies the clusters. The system achieves a promising diarization error rate (DER) of 16.4%.
Bibliographic reference. Nwe, Tin Lay / Sun, Hanwu / Ma, Bin / Li, Haizhou (2010): "Speaker diarization in meeting audio for single distant microphone", In INTERSPEECH-2010, 1505-1508.