9 citations · 48 across the 9 of their papers we have counts for
9 papers
Anomalous Sound Detection as a Simple Binary Classification Problem with Careful Selection of Proxy Outlier Examples
Paul Primus, Verena Haunschmid, Patrick Praher +1
Unsupervised anomalous sound detection is concerned with identifying sounds that deviate from what is defined as 'normal', without explicitly specifying the types of anomalies. A s…
audioLIME: Listenable Explanations Using Source Separation
Verena Haunschmid, Ethan Manilow, Gerhard Widmer
Deep neural networks (DNNs) are successfully applied in a wide variety of music information retrieval (MIR) tasks but their predictions are usually not interpretable. We propose au…
Towards Musically Meaningful Explanations Using Source Separation
Verena Haunschmid, Ethan Manilow, Gerhard Widmer
Deep neural networks (DNNs) are successfully applied in a wide variety of music information retrieval (MIR) tasks. Such models are usually considered "black boxes", meaning that th…
Receptive-Field Regularized CNNs for Music Classification and Tagging
Khaled Koutini, Hamid Eghbal-Zadeh, Verena Haunschmid +3
Convolutional Neural Networks (CNNs) have been successfully used in various Music Information Retrieval (MIR) tasks, both as end-to-end models and as feature extractors for more co…
On Data Augmentation and Adversarial Risk: An Empirical Analysis
Hamid Eghbal-zadeh, Khaled Koutini, Paul Primus +5
Data augmentation techniques have become standard practice in deep learning, as it has been shown to greatly improve the generalisation abilities of models. These techniques rely o…
Emotion and Theme Recognition in Music with Frequency-Aware RF-Regularized CNNs
Khaled Koutini, Shreyan Chowdhury, Verena Haunschmid +2
We present CP-JKU submission to MediaEval 2019; a Receptive Field-(RF)-regularized and Frequency-Aware CNN approach for tagging music with emotion/mood labels. We perform an invest…
Towards Explainable Music Emotion Recognition: The Route via Mid-level Features
Shreyan Chowdhury, Andreu Vall, Verena Haunschmid +1
Emotional aspects play an important part in our interaction with music. However, modelling these aspects in MIR systems have been notoriously challenging since emotion is an inhere…
Two-level Explanations in Music Emotion Recognition
Verena Haunschmid, Shreyan Chowdhury, Gerhard Widmer
Current ML models for music emotion recognition, while generally working quite well, do not give meaningful or intuitive explanations for their predictions. In this work, we propos…
An Evolutionary Stochastic-Local-Search Framework for One-Dimensional Cutting-Stock Problems
Georgios C. Chasparis, Michael Rossbory, Verena Haunschmid
We introduce an evolutionary stochastic-local-search (SLS) algorithm for addressing a generalized version of the so-called 1/V/D/R cutting-stock problem. Cutting-stock problems are…