Deep neural networks (DNNs) have introduced novel and useful tools to the machine
learning community. Other types of classifiers can potentially make use of these tools as well …

We present an approach to encode a speech signal into a fixed-size representation which
minimizes the cosine loss with the existing massively multilingual LASER text embedding …

Early changes in infants' ability to perceive native and nonnative speech sound contrasts are
typically attributed to their develo** knowledge of phonetic categories. We critically …

Finding word boundaries in continuous speech is challenging as there is little or no
equivalent of a 'space'delimiter between words. Popular Bayesian non-parametric models …

We consider feature learning for a computationally efficient method of keyword spotting that
can be applied in severely under-resourced settings. The objective is to support …

We propose an end-to-end deep model for speaker verification in the wild. Our model uses
thin-ResNet for extracting speaker embeddings from utterances and a Siamese capsule …

Acoustic word embeddings are fixed-dimensional representations of variable-length speech
segments. Such embeddings can form the basis for speech search, indexing and discovery …