Two's a crowd: improving speaker diarization by automatically identifying and excluding overlapped speech

Abstract

We present an update to our initial work [1] on overlapped speech detection for improving speaker diarization. Specifi-cally, we describe the addition of new features and feature warp-ing techniques that improve segmenter and, consequently, di-arization performance. We also demonstrate improved diariza-tion performance by additionally using overlap segment infor-mation in a new diarization pre-processing step which excludes overlap segments from speaker clustering. On a subset of the AMI Meeting Corpus we show that this overlap exclusion step nearly triples the relative improvement of diarization error rate as compared to overlap segment post-processing alone. Index Terms: speaker diarization, overlap detection 1.