148 citations · 209 across the 6 of their papers we have counts for
6 papers
wav2pos: Sound Source Localization using Masked Autoencoders
Axel Berg, Jens Gulin, Mark O'Connor +3
We present a novel approach to the 3D sound source localization task for distributed ad-hoc microphone arrays by formulating it as a set-to-set regression problem. By training a mu…
Extending GCC-PHAT using Shift Equivariant Neural Networks
Axel Berg, Mark O'Connor, Kalle Åström +1
Speaker localization using microphone arrays depends on accurate time delay estimation techniques. For decades, methods based on the generalized cross correlation with phase transf…
Points to Patches: Enabling the Use of Self-Attention for 3D Shape Recognition
Axel Berg, Magnus Oskarsson, Mark O'Connor
While the Transformer architecture has become ubiquitous in the machine learning field, its adaptation to 3D shape recognition is non-trivial. Due to its quadratic computational co…
Keyword Transformer: A Self-Attention Model for Keyword Spotting
Axel Berg, Mark O'Connor, Miguel Tairum Cruz
The Transformer architecture has been successful across many domains, including natural language processing, computer vision and speech recognition. In keyword spotting, self-atten…
Deep Ordinal Regression with Label Diversity
Axel Berg, Magnus Oskarsson, Mark O'Connor
Regression via classification (RvC) is a common method used for regression problems in deep learning, where the target variable belongs to a set of continuous values. By discretizi…
Variance Constrained Autoencoding
D. T. Braithwaite, M. O'Connor, W. B. Kleijn
Recent state-of-the-art autoencoder based generative models have an encoder-decoder structure and learn a latent representation with a pre-defined distribution that can be sampled…