2 papers
eess.AS2021
Semi-Supervised Training with Pseudo-Labeling for End-to-End Neural Diarization
Yuki Takashima, Yusuke Fujita, Shota Horiguchi +3
In this paper, we present a semi-supervised training technique using pseudo-labeling for end-to-end neural diarization (EEND). The EEND system has shown promising performance compa…
eess.AS2019
Feature Enhancement with Deep Feature Losses for Speaker Verification
Saurabh Kataria, Phani Sankar Nidadavolu, Jesús Villalba +3
Speaker Verification still suffers from the challenge of generalization to novel adverse environments. We leverage on the recent advancements made by deep learning based speech enh…