859 citations · 1.5k across the 35 of their papers we have counts for
9 papers · 1 filter
Separation of Moving Sound Sources Using Multichannel NMF and Acoustic Tracking
Joonas Nikunen, Aleksandr Diment, Tuomas Virtanen
In this paper we propose a method for separation of moving sound sources. The method is based on first tracking the sources and then estimation of source spectrograms using multich…
Sound event detection using weakly labeled dataset with stacked convolutional and recurrent neural network
Sharath Adavanne, Tuomas Virtanen
This paper proposes a neural network architecture and training scheme to learn the start and end time of sound events (strong labels) in an audio recording given just the list of s…
A report on sound event detection with different binaural features
Sharath Adavanne, Tuomas Virtanen
In this paper, we compare the performance of using binaural audio features in place of single-channel features for sound event detection. Three different binaural features are stud…
Sound Event Detection in Multichannel Audio Using Spatial and Harmonic Features
Sharath Adavanne, Giambattista Parascandolo, Pasi Pertilä +2
In this paper, we propose the use of spatial and harmonic features in combination with long short term memory (LSTM) recurrent neural network (RNN) for automatic sound event detect…
Stacked Convolutional and Recurrent Neural Networks for Music Emotion Recognition
Miroslav Malik, Sharath Adavanne, Konstantinos Drossos +3
This paper studies the emotion recognition from musical tracks in the 2-dimensional valence-arousal (V-A) emotional space. We propose a method based on convolutional (CNN) and recu…
Sound Event Detection Using Spatial Features and Convolutional Recurrent Neural Network
Sharath Adavanne, Pasi Pertilä, Tuomas Virtanen
This paper proposes to use low-level spatial features extracted from multichannel audio for sound event detection. We extend the convolutional recurrent neural network to handle mo…