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This paper describes the winning systems developed by the BUT team for thefour tracks of the Second DIHARD Speech Diarization Challenge. For tracks 1 and2 the systems were mainly based on performing agglomerative hierarchicalclustering (AHC) of x-vectors, followed by another x-vector clustering based onBayes hidden Markov model and variational Bayes inference. We provide acomparison of the improvement given by each step and share the implementationof the core of the system. For tracks 3 and 4 with recordings from the FifthCHiME Challenge, we explored different approaches for doing multi-channeldiarization and our best performance was obtained when applying AHC on thefusion of per channel probabilistic linear discriminant analysis scores.

BUT System for the Second DIHARD Speech Diarization Challenge