activity
20142021
most citedUnsupervised Feature Learning Based on Deep Models for Environmental Audio Tagging

86 citations · 126 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CR2021

SK-Tree: a systematic malware detection algorithm on streaming trees via the signature kernel

Thomas Cochrane, Peter Foster, Varun Chhabra +3

The development of machine learning algorithms in the cyber security domain has been impeded by the complex, hierarchical, sequential and multimodal nature of the data involved. In…

cs.LG2020★ 3 cited

Dimensionless Anomaly Detection on Multivariate Streams with Variance Norm and Path Signature

Zhen Shao, Ryan Sze-Yin Chan, Thomas Cochrane +2

In this paper, we propose a dimensionless anomaly detection method for multivariate streams. Our method is independent of the unit of measurement for the different stream channels,…

cs.SD2016★ 86 cited

Unsupervised Feature Learning Based on Deep Models for Environmental Audio Tagging

Yong Xu, Qiang Huang, Wenwu Wang +4

Environmental audio tagging aims to predict only the presence or absence of certain acoustic events in the interested acoustic scene. In this paper we make contributions to audio t…

cs.IR2014★ 26 cited

Identifying Cover Songs Using Information-Theoretic Measures of Similarity

Peter Foster, Simon Dixon, Anssi Klapuri

This paper investigates methods for quantifying similarity between audio signals, specifically for the task of of cover song detection. We consider an information-theoretic approac…

cs.IR2014★ 11 cited

Sequential Complexity as a Descriptor for Musical Similarity

Peter Foster, Matthias Mauch, Simon Dixon

We propose string compressibility as a descriptor of temporal structure in audio, for the purpose of determining musical similarity. Our descriptors are based on computing track-wi…