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Found 16 papers, 5 papers with code
Toroidal Probabilistic Spherical Discriminant Analysis
It extends PSDA with the ability to model within and between-speaker variabilities in toroidal submanifolds of the hypersphere.
Probabilistic Spherical Discriminant Analysis: An Alternative to PLDA for length-normalized embeddings
In speaker recognition, where speech segments are mapped to embeddings on the unit hypersphere, two scoring backends are commonly used, namely cosine scoring or PLDA.
How to use KL-divergence to construct conjugate priors, with well-defined non-informative limits, for the multivariate Gaussian
The Wishart distribution is the standard conjugate prior for the precision of the multivariate Gaussian likelihood, when the mean is known -- while the normal-Wishart can be used when the mean is also unknown.
The Phonexia VoxCeleb Speaker Recognition Challenge 2021 System Description
We describe the Phonexia submission for the VoxCeleb Speaker Recognition Challenge 2021 (VoxSRC-21) in the unsupervised speaker verification track.
Out of a hundred trials, how many errors does your speaker verifier make?
For perfect calibration, the Bayes error-rate is upper bounded by min(EER, P, 1-P), where EER is the equal-error-rate and P, 1-P are the prior probabilities of the competing hypotheses.
Probabilistic embeddings for speaker diarization
We apply the proposed probabilistic embeddings as input to an agglomerative hierarchical clustering (AHC) algorithm to do diarization in the DIHARD'19 evaluation set.
Language-depedent I-Vectors for LRE15
A standard recipe for spoken language recognition is to apply a Gaussian back-end to i-vectors.
Note on the equivalence of hierarchical variational models and auxiliary deep generative models
This note compares two recently published machine learning methods for constructing flexible, but tractable families of variational hidden-variable posteriors.
VB calibration to improve the interface between phone recognizer and i-vector extractor
We show here that the classical i-vector extractor recipe is actually a mean-field variational Bayes (VB) recipe.
Constrained speaker linking
In this paper we study speaker linking (a. k. a.\ partitioning) given constraints of the distribution of speaker identities over speech recordings.
Bayesian calibration for forensic evidence reporting
We introduce a Bayesian solution for the problem in forensic speaker recognition, where there may be very little background material for estimating score calibration parameters.
A comparison of linear and non-linear calibrations for speaker recognition
In recent work on both generative and discriminative score to log-likelihood-ratio calibration, it was shown that linear transforms give good accuracy only for a limited range of operating points.
The EM algorithm and the Laplace Approximation
The Laplace approximation calls for the computation of second derivatives at the likelihood maximum.
Generative Modelling for Unsupervised Score Calibration
Score calibration enables automatic speaker recognizers to make cost-effective accept / reject decisions.
Likelihood-ratio calibration using prior-weighted proper scoring rules
Prior-weighted logistic regression has become a standard tool for calibration in speaker recognition.
The BOSARIS Toolkit: Theory, Algorithms and Code for Surviving the New DCF
This poses the challenges of (i) how to decide what number of trials is enough, and (ii) how to process such large data sets with reasonable memory and CPU requirements.
