Fusion of heterogeneous speaker recognition systems in the STBU submission for the NIST speaker recognition evaluation 2006
INTERSPEECH 2009 Abstract: Brümmer et al.
Niko Brummer Primêre Skool | Beaufort West
PDF) Gaussian meta-embeddings for efficient scoring of a heavy-tailed PLDA model
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VGS Invited Talks @ FIT | Invited Talks on Vision, Graphics, and Speech at Faculty of Information Technology, Brno University of Technology
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![PDF] Support vector machines versus fast scoring in the low-dimensional total variability space for speaker verification](https://i1.rgstatic.net/publication/221483664_Support_vector_machines_versus_fast_scoring_in_the_low-dimensional_total_variability_space_for_speaker_verification/links/0deec517677717d9b3000000/largepreview.png "PDF] Support vector machines versus fast scoring in the low-dimensional total variability space for speaker verification")
PDF] Support vector machines versus fast scoring in the low-dimensional total variability space for speaker verification
Odyssey 2010 Welcome Message
Anna Silnova | DeepAI
Anna Silnova | DeepAI
PDF) Fully Bayesian Likelihood Ratios vs i-vector Length Normalization in Speaker Recognition Systems | ResearchGate
Niko Brummer Primêre Skool | Beaufort West
Gaussian meta-embeddings for efficient scoring of a heavy-tailed PLDA model
PDF) Discriminative acoustic language recognition via channel-compensated GMM statistics
Jun 2022 – Union Schools
The BOSARIS Toolkit: Theory, Algorithms and Code for Surviving the New DCF | DeepAI
Niko Brummer Primêre Skool | Beaufort West
Jun 2022 – Union Schools
Reviewer Acknowledgement
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