The systems were trained in Kaldi toolkit [14] using SRE16 recipe with modiﬁcations described below: • Using different feature sets • Training networks with 9 epochs (instead of 3)

x-vector Systems All x-vectors used V AD-Energy from Kaldi SRE16 recipe 6

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eess.AS · 2019-07-13 · unverdicted · novelty 3.0

BUT reports x-vector systems achieving 1.0% EER via fusion on the fixed condition of the VOiCES 2019 speaker recognition challenge.

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BUT VOiCES 2019 System Description eess.AS · 2019-07-13 · unverdicted · none · ref 4
BUT reports x-vector systems achieving 1.0% EER via fusion on the fixed condition of the VOiCES 2019 speaker recognition challenge.