2 citations · 2 across the 3 of their papers we have counts for
3 papers · 1 filter
Clustering-based hard negative sampling for supervised contrastive speaker verification
Piotr Masztalski, Michał Romaniuk, Jakub Żak +2
In speaker verification, contrastive learning is gaining popularity as an alternative to the traditionally used classification-based approaches. Contrastive methods can benefit fro…
Refining DNN-based Mask Estimation using CGMM-based EM Algorithm for Multi-channel Noise Reduction
Julitta Bartolewska, Stanisław Kacprzak, Konrad Kowalczyk
In this paper, we present a method that allows to further improve speech enhancement obtained with recently introduced Deep Neural Network (DNN) models. We propose a multi-channel…
Causal Signal-Based DCCRN with Overlapped-Frame Prediction for Online Speech Enhancement
Julitta Bartolewska, Stanisław Kacprzak, Konrad Kowalczyk
The aim of speech enhancement is to improve speech signal quality and intelligibility from a noisy microphone signal. In many applications, it is crucial to enable processing with…