Program
Large-Scale Evaluation of Short-Duration Speaker Verification
Mon-SS-2-6-8 BUT Text-Dependent Speaker Verification System for SdSV Challenge 2020
Alicia Lozano-Diez(Brno University of Technology), Anna Silnova(Brno University of Technology), Bhargav Pulugundla(Brno University of Technology), Johan Rohdin(Brno University of Technology), Karel Vesely(Brno University of Technology), Lukas Burget(Brno University of Technology), Oldrich Plchot(Brno University of Technology), Ondrej Glembek(Brno University of Technology), Ondrej Novotny(Brno University of Technology) and Pavel Matejka(Brno University of Technology)
Abstract:
In this paper, we present the winning BUT submission for the text-dependent task of the SdSV challenge 2020. Given the large amount of training data available in this challenge, we explore successful techniques from text-independent systems in the text-dependent scenario. In particular, we trained x-vector extractors on both in-domain and out-domain datasets and combine them with i-vectors trained on concatenated MFCCs and bottleneck features, which have proven effective for the text-dependent scenario. Moreover, we proposed the use of phrase-dependent PLDA backend for scoring and its combination with a simple phrase recognizer, which brings up to 63% relative improvement on our development set with respect to using standard PLDA. Finally, we combine our different i-vector and x-vector based systems using a simple linear logistic regression score level fusion, which provides 28% relative improvement on the evaluation set with respect to our best single system.
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