A TIC-MRF approach to speaker clustering on i-vectors yields relative DER reductions of 43.22% on CRSS-PLTL and 29.37%/9.21% on two AMI meetings versus cosine K-means and movMF baselines.
Speaker recognition by machines and humans: A tutorial review
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2019 2verdicts
UNVERDICTED 2representative citing papers
Residual neural network on speed-perturbed group delay features achieves 1.08% EER on ASVspoof 2019 evaluation set for physical access replay detection.
citing papers explorer
-
Toeplitz Inverse Covariance based Robust Speaker Clustering for Naturalistic Audio Streams
A TIC-MRF approach to speaker clustering on i-vectors yields relative DER reductions of 43.22% on CRSS-PLTL and 29.37%/9.21% on two AMI meetings versus cosine K-means and movMF baselines.
-
The DKU Replay Detection System for the ASVspoof 2019 Challenge: On Data Augmentation, Feature Representation, Classification, and Fusion
Residual neural network on speed-perturbed group delay features achieves 1.08% EER on ASVspoof 2019 evaluation set for physical access replay detection.