17 citations · 46 across the 22 of their papers we have counts for
8 papers · 1 filter
TransFusion: Transcribing Speech with Multinomial Diffusion
Matthew Baas, Kevin Eloff, Herman Kamper
Diffusion models have shown exceptional scaling properties in the image synthesis domain, and initial attempts have shown similar benefits for applying diffusion to unconditional t…
Feature learning for efficient ASR-free keyword spotting in low-resource languages
Ewald van der Westhuizen, Herman Kamper, Raghav Menon +2
We consider feature learning for efficient keyword spotting that can be applied in severely under-resourced settings. The objective is to support humanitarian relief programmes by…
Analyzing Speaker Information in Self-Supervised Models to Improve Zero-Resource Speech Processing
Benjamin van Niekerk, Leanne Nortje, Matthew Baas +1
Contrastive predictive coding (CPC) aims to learn representations of speech by distinguishing future observations from a set of negative examples. Previous work has shown that line…
StarGAN-ZSVC: Towards Zero-Shot Voice Conversion in Low-Resource Contexts
Matthew Baas, Herman Kamper
Voice conversion is the task of converting a spoken utterance from a source speaker so that it appears to be said by a different target speaker while retaining the linguistic conte…
A Correspondence Variational Autoencoder for Unsupervised Acoustic Word Embeddings
Puyuan Peng, Herman Kamper, Karen Livescu
We propose a new unsupervised model for mapping a variable-duration speech segment to a fixed-dimensional representation. The resulting acoustic word embeddings can form the basis…
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…