The ICSI RT07s Speaker Diarization System

Abstract. In this paper, we present the ICSI speaker diarization system. This system was used in the 2007 National Institute of Standards and Technology (NIST) Rich Transcription evaluation. The ICSI system automatically performs both speaker segmentation and clustering without any prior knowledge of the identities or the number of speakers. Our system uses “standard” speech processing components and techniques such as HMMs, agglomerative clustering, and the Bayesian Information Criterion. However, we have developed the system with an eye towards robustness and ease of portability. Thus we have avoided the use of any sort of model that requires training on “outside” data and we have attempted to develop algorithms that require as little tuning as possible. The system is simular to last year’s system [1] except for three aspects. We used the most recent available version of the beam-forming toolkit, we implemented a new speech/non-speech detector that does not require models t...

• Type: Conference
• Year: 2007
• Where: CLEAR
• Authors: Chuck Wooters, Marijn Huijbregts
• Keywords: Bayesian Information Criterion, Biometrics, CLEAR 2007, ICSI Speaker Diarization, Rich Transcription Evaluation