Iwona Sobieraj — accepted AI-conference papers

2019

Acoustic Event Detection from Weakly Labeled Data Using Auditory Salience

Zuzanna Podwinska, Iwona Sobieraj, Bruno M. Fazenda, William J. Davies, Mark D. Plumbley

ICASSP 2019accepted

Acoustic Event Detection (AED) is an important task of machine listening which, in recent years, has been addressed using common machine learning methods like Non-negative Matrix Factorization (NMF) or deep learning. However, most of these approaches do not take into consideration the way that human…

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2018

Orthogonality-Regularized Masked NMF for Learning on Weakly Labeled Audio Data

Iwona Sobieraj, Lucas Rencker, Mark D. Plumbley

ICASSP 2018accepted

Non-negative Matrix Factorization (NMF) is a well established tool for audio analysis. However, it is not well suited for learning on weakly labeled data, i.e. data where the exact timestamp of the sound of interest is not known. In this paper we propose a novel extension to NMF, that allows it to e…

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