111 citations · 133 across the 7 of their papers we have counts for
5 papers · 1 filter
Interpreting Speaker Characteristics in the Dimensions of Self-Supervised Speech Features
Kyle Janse van Rensburg, Benjamin van Niekerk, Herman Kamper
How do speech models trained through self-supervised learning structure their representations? Previous studies have looked at how information is encoded in feature vectors across…
Revisiting speech segmentation and lexicon learning with better features
Herman Kamper, Benjamin van Niekerk
We revisit a self-supervised method that segments unlabelled speech into word-like segments. We start from the two-stage duration-penalised dynamic programming method that performs…
Rhythm Modeling for Voice Conversion
Benjamin van Niekerk, Marc-André Carbonneau, Herman Kamper
Voice conversion aims to transform source speech into a different target voice. However, typical voice conversion systems do not account for rhythm, which is an important factor in…
Voice Conversion With Just Nearest Neighbors
Matthew Baas, Benjamin van Niekerk, Herman Kamper
Any-to-any voice conversion aims to transform source speech into a target voice with just a few examples of the target speaker as a reference. Recent methods produce convincing con…
A Comparison of Discrete and Soft Speech Units for Improved Voice Conversion
Benjamin van Niekerk, Marc-André Carbonneau, Julian Zaïdi +3
The goal of voice conversion is to transform source speech into a target voice, keeping the content unchanged. In this paper, we focus on self-supervised representation learning fo…