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• W2400670753 abstract "In some situations the quality of the signals involved in a speaker verification trial is not as good as needed to take a reliable decision. In this work, we present a new method based on Bayesian networks and quality measures to estimate if the trial decision is reliable. We present experiments on the NIST SRE2010 dataset degraded with additive noise. A system well calibrated for clean speech, produces a large actual DCF on the degraded dataset. We use our method to discard the unreliable trials and achieve a dramatic improvement of the cost values. We also prove that our method outperforms previously published approaches." @default.
• W2400670753 created "2016-06-24" @default.
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• W2400670753 date "2013-08-25" @default.
• W2400670753 modified "2023-10-18" @default.
• W2400670753 title "A new Bayesian network to assess the reliability of speaker verification decisions" @default.
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• W2400670753 doi "https://doi.org/10.21437/interspeech.2013-682" @default.
• W2400670753 hasPublicationYear "2013" @default.
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