33 citations · 54 across the 5 of their papers we have counts for
5 papers
DropClass and DropAdapt: Dropping classes for deep speaker representation learning
Chau Luu, Peter Bell, Steve Renals
Many recent works on deep speaker embeddings train their feature extraction networks on large classification tasks, distinguishing between all speakers in a training set. Empirical…
Dynamic Evaluation of Transformer Language Models
Ben Krause, Emmanuel Kahembwe, Iain Murray +1
This research note combines two methods that have recently improved the state of the art in language modeling: Transformers and dynamic evaluation. Transformers use stacked layers…
Multi-view Dimensionality Reduction for Dialect Identification of Arabic Broadcast Speech
Sameer Khurana, Ahmed Ali, Steve Renals
In this work, we present a new Vector Space Model (VSM) of speech utterances for the task of spoken dialect identification. Generally, DID systems are built using two sets of featu…
Knowledge Distillation for Small-footprint Highway Networks
Liang Lu, Michelle Guo, Steve Renals
Deep learning has significantly advanced state-of-the-art of speech recognition in the past few years. However, compared to conventional Gaussian mixture acoustic models, neural ne…
Tied Probabilistic Linear Discriminant Analysis for Speech Recognition
Liang Lu, Steve Renals
Acoustic models using probabilistic linear discriminant analysis (PLDA) capture the correlations within feature vectors using subspaces which do not vastly expand the model. This a…