55 citations · 84 across the 17 of their papers we have counts for
4 papers · 1 filter
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…
Receptive-field-regularized CNN variants for acoustic scene classification
Khaled Koutini, Hamid Eghbal-zadeh, Gerhard Widmer
Acoustic scene classification and related tasks have been dominated by Convolutional Neural Networks (CNNs). Top-performing CNNs use mainly audio spectograms as input and borrow th…
Exploiting Parallel Audio Recordings to Enforce Device Invariance in CNN-based Acoustic Scene Classification
Paul Primus, Hamid Eghbal-zadeh, David Eitelsebner +3
Distribution mismatches between the data seen at training and at application time remain a major challenge in all application areas of machine learning. We study this problem in th…
The Receptive Field as a Regularizer in Deep Convolutional Neural Networks for Acoustic Scene Classification
Khaled Koutini, Hamid Eghbal-zadeh, Matthias Dorfer +1
Convolutional Neural Networks (CNNs) have had great success in many machine vision as well as machine audition tasks. Many image recognition network architectures have consequently…