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 tutorial on deep learning for music information retrieval
Following their success in Computer Vision and other areas, deep learning techniques have
recently become widely adopted in Music Information Retrieval (MIR) research. However …
recently become widely adopted in Music Information Retrieval (MIR) research. However …
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 …
MT3: Multi-task multitrack music transcription
Automatic Music Transcription (AMT), inferring musical notes from raw audio, is a
challenging task at the core of music understanding. Unlike Automatic Speech Recognition …
challenging task at the core of music understanding. Unlike Automatic Speech Recognition …
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 …
Video2music: Suitable music generation from videos using an affective multimodal transformer model
Numerous studies in the field of music generation have demonstrated impressive
performance, yet virtually no models are able to directly generate music to match …
performance, yet virtually no models are able to directly generate music to match …
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 …
Hear: Holistic evaluation of audio representations
What audio embedding approach generalizes best to a wide range of downstream tasks
across a variety of everyday domains without fine-tuning? The aim of the HEAR benchmark …
across a variety of everyday domains without fine-tuning? The aim of the HEAR benchmark …
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 …
ASAP: a dataset of aligned scores and performances for piano transcription
In this paper we present Aligned Scores and Performances (ASAP): a new dataset of 222
digital musical scores aligned with 1068 performances (more than 92 hours) of Western …
digital musical scores aligned with 1068 performances (more than 92 hours) of Western …