Music Information Retrieval (MIR) has seen a recent surge in deep
learni...
Previous research has shown that established techniques for spoken voice...
Lyric interpretations can help people understand songs and their lyrics
...
Disentangled sequential autoencoders (DSAEs) represent a class of
probab...
Performance-score synchronization is an integral task in signal processi...
In this paper we propose modifications to the neural network framework,
...
Sixty participants provided dissimilarity ratings between various singin...
This paper makes several contributions to automatic lyrics transcription...
This paper proposes a deep convolutional neural network for performing
n...
Recent automatic lyrics transcription (ALT) approaches focus on building...
Lyrics alignment in long music recordings can be memory exhaustive when
...
The identification of structural differences between a music performance...
This paper addresses the problem of domain adaptation for the task of mu...
Audio-to-score alignment aims at generating an accurate mapping between ...
Audio-to-score alignment aims at generating an accurate mapping between ...
Speech recognition is a well developed research field so that the curren...
One way to analyse the behaviour of machine learning models is through l...
Convolutional neural networks (CNNs) with dilated filters such as the Wa...
Generative adversarial networks (GANs) have shown great success in
appli...
In this paper we propose an efficient deep learning encoder-decoder netw...
One way to interpret trained deep neural networks (DNNs) is by inspectin...
Models for audio source separation usually operate on the magnitude spec...
A main challenge in applying deep learning to music processing is the
av...
The expressive nature of the voice provides a powerful medium for
commun...
The state of the art in music source separation employs neural networks
...
We present a supervised neural network model for polyphonic piano music
...
This paper investigates methods for quantifying similarity between audio...