Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Microsoft Speaker Diarization System for the VoxCeleb Speaker
  Recognition Challenge 2020   This paper describes the Microsoft speaker diarization system for monaural
multi-talker recordings in the wild, evaluated at the diarization track of the
VoxCeleb Speaker Recognition Challenge(VoxSRC) 2020. We will first explain our
system design to address issues in handling real multi-talker recordings. We
then present the details of the components, which include Res2Net-based speaker
embedding extractor, conformer-based continuous speech separation with leakage
filtering, and a modified DOVER (short for Diarization Output Voting Error
Reduction) method for system fusion. We evaluate the systems with the data set
provided by VoxSRCchallenge 2020, which contains real-life multi-talker audio
collected from YouTube. Our best system achieves 3.71% and 6.23% of the
diarization error rate (DER) on development set and evaluation set,
respectively, being ranked the 1st at the diarization track of the challenge.

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The categories of this paper are: hep-th
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The categories of this paper are: astro-ph
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The categories of this paper are: patt-sol
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The categories of this paper are: q-bio
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The categories of this paper are: q-fin
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The categories of this paper are: mtrl-th
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The categories of this paper are: solv-int
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The categories of this paper are: chem-ph
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The categories of this paper are: hep-lat
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The categories of this paper are: atom-ph
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The categories of this paper are: acc-phys
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The categories of this paper are: nlin
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The categories of this paper are: hep-ex
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The categories of this paper are: q-alg
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The categories of this paper are: quant-ph
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The categories of this paper are: hep-ph