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This paper describes the systems developed by the BUT team for the fourtracks of the second DIHARD speech diarization challenge. For tracks 1 and 2the systems were based on performing agglomerative hierarchical clustering(AHC) over x-vectors, followed by the Bayesian Hidden Markov Model (HMM) witheigenvoice priors applied at x-vector level followed by the same approachapplied at frame level. For tracks 3 and 4, the systems were based onperforming AHC using x-vectors extracted on all channels.

BUT System Description for DIHARD Speech Diarization Challenge 2019