Automatic music transcription: An overview
The capability of transcribing music audio into music notation is a fascinating example of
human intelligence. It involves perception (analyzing complex auditory scenes), cognition …
human intelligence. It involves perception (analyzing complex auditory scenes), cognition …
A review of automatic drum transcription
In Western popular music, drums and percussion are an important means to emphasize and
shape the rhythm, often defining the musical style. If computers were able to analyze the …
shape the rhythm, often defining the musical style. If computers were able to analyze the …
Origins of music in credible signaling
Music comprises a diverse category of cognitive phenomena that likely represent both the
effects of psychological adaptations that are specific to music (eg, rhythmic entrainment) and …
effects of psychological adaptations that are specific to music (eg, rhythmic entrainment) and …
Onsets and frames: Dual-objective piano transcription
We advance the state of the art in polyphonic piano music transcription by using a deep
convolutional and recurrent neural network which is trained to jointly predict onsets and …
convolutional and recurrent neural network which is trained to jointly predict onsets and …
Internet of musical things: Vision and challenges
The Internet of Musical Things (IoMusT) is an emerging research field positioned at the
intersection of Internet of Things, new interfaces for musical expression, ubiquitous music …
intersection of Internet of Things, new interfaces for musical expression, ubiquitous music …
[HTML][HTML] Speech emotion recognition using fusion of three multi-task learning-based classifiers: HSF-DNN, MS-CNN and LLD-RNN
Speech emotion recognition plays an increasingly important role in emotional computing
and is still a challenging task due to its complexity. In this study, we developed a framework …
and is still a challenging task due to its complexity. In this study, we developed a framework …
High-resolution piano transcription with pedals by regressing onset and offset times
Automatic music transcription (AMT) is the task of transcribing audio recordings into
symbolic representations. Recently, neural network-based methods have been applied to …
symbolic representations. Recently, neural network-based methods have been applied to …
Learning features of music from scratch
This paper introduces a new large-scale music dataset, MusicNet, to serve as a source of
supervision and evaluation of machine learning methods for music research. MusicNet …
supervision and evaluation of machine learning methods for music research. MusicNet …
Novel audio features for music emotion recognition
This work advances the music emotion recognition state-of-the-art by proposing novel
emotionally-relevant audio features. We reviewed the existing audio features implemented …
emotionally-relevant audio features. We reviewed the existing audio features implemented …
nnaudio: An on-the-fly gpu audio to spectrogram conversion toolbox using 1d convolutional neural networks
In this paper, we present nnAudio, a new neural network-based audio processing framework
with graphics processing unit (GPU) support that leverages 1D convolutional neural …
with graphics processing unit (GPU) support that leverages 1D convolutional neural …