10 citations · 14 across the 7 of their papers we have counts for
4 papers · 1 filter
Towards localisation of keywords in speech using weak supervision
Kayode Olaleye, Benjamin van Niekerk, Herman Kamper
Developments in weakly supervised and self-supervised models could enable speech technology in low-resource settings where full transcriptions are not available. We consider whethe…
Towards unsupervised phone and word segmentation using self-supervised vector-quantized neural networks
Herman Kamper, Benjamin van Niekerk
We investigate segmenting and clustering speech into low-bitrate phone-like sequences without supervision. We specifically constrain pretrained self-supervised vector-quantized (VQ…
Vector-quantized neural networks for acoustic unit discovery in the ZeroSpeech 2020 challenge
Benjamin van Niekerk, Leanne Nortje, Herman Kamper
In this paper, we explore vector quantization for acoustic unit discovery. Leveraging unlabelled data, we aim to learn discrete representations of speech that separate phonetic con…
Online Constrained Model-based Reinforcement Learning
Benjamin van Niekerk, Andreas Damianou, Benjamin Rosman
Applying reinforcement learning to robotic systems poses a number of challenging problems. A key requirement is the ability to handle continuous state and action spaces while remai…