The IIR NIST SRE 2008 and 2010 summed channel speaker recognition systems

Abstract

This paper reports the IIR speaker recognition system for the summed channel evaluation tasks in the NIST SRE 2008 and 2010. The system includes three main modules: voice activity detection, speaker diarization and speaker recognition. The front-end process employs a voice activity detection algorithm for effective speech frame selection. The speaker diarization system that was developed for 2007 and 2009 NIST RT Evaluations is adopted for summed channel speech segmentation. A hybrid purifying and clustering algorithm is developed to segregate the summed channel speech by speakers. The GMM-SVM speaker recognition system is adopted to evaluate the performance with both MFCC and LPCC features. The system achieves an overall EER of 3.46% in the 1conv-summed task and 1.87% in the 8conv-summed task, respectively, where only all English trials are involved.