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Speaker diarization via unsupervised i-vector clustering has gained popularity in recent years. In this approach, i-vectors are extracted from short clips of speech segmented from a larger multi-speaker conversation and organized into speaker clusters, typically according to their cosine score. In this paper, we propose a system that incorporates… CONTINUE READING