A comprehensive survey on deep music generation: Multi-level representations, algorithms, evaluations, and future directions
S Ji, J Luo, X Yang - arxiv preprint arxiv:2011.06801, 2020 - arxiv.org
The utilization of deep learning techniques in generating various contents (such as image,
text, etc.) has become a trend. Especially music, the topic of this paper, has attracted …
text, etc.) has become a trend. Especially music, the topic of this paper, has attracted …
An overview of lead and accompaniment separation in music
Popular music is often composed of an accompaniment and a lead component, the latter
typically consisting of vocals. Filtering such mixtures to extract one or both components has …
typically consisting of vocals. Filtering such mixtures to extract one or both components has …
Singing voice separation with deep u-net convolutional networks
The decomposition of a music audio signal into its vocal and backing track components is
analogous to image-to-image translation, where a mixed spectrogram is transformed into its …
analogous to image-to-image translation, where a mixed spectrogram is transformed into its …
The 2016 signal separation evaluation campaign
In this paper, we report the results of the 2016 community-based Signal Separation
Evaluation Campaign (SiSEC 2016). This edition comprises four tasks. Three focus on the …
Evaluation Campaign (SiSEC 2016). This edition comprises four tasks. Three focus on the …
Creating a multitrack classical music performance dataset for multimodal music analysis: Challenges, insights, and applications
We introduce a dataset for facilitating audio-visual analysis of music performances. The
dataset comprises 44 simple multi-instrument classical music pieces assembled from …
dataset comprises 44 simple multi-instrument classical music pieces assembled from …
Cutting music source separation some Slakh: A dataset to study the impact of training data quality and quantity
Music source separation performance has greatly improved in recent years with the advent
of approaches based on deep learning. Such methods typically require large amounts of …
of approaches based on deep learning. Such methods typically require large amounts of …
Musical source separation: An introduction
Many people listen to recorded music as part of their everyday lives, eg, from radio or TV
programs, compact discs, downloads, or, increasingly, online streaming services …
programs, compact discs, downloads, or, increasingly, online streaming services …
Moisesdb: A dataset for source separation beyond 4-stems
In this paper, we introduce the MoisesDB dataset for musical source separation. It consists of
240 tracks from 45 artists, covering twelve musical genres. For each song, we provide its …
240 tracks from 45 artists, covering twelve musical genres. For each song, we provide its …
Joint detection and classification of singing voice melody using convolutional recurrent neural networks
Singing melody extraction essentially involves two tasks: one is detecting the activity of a
singing voice in polyphonic music, and the other is estimating the pitch of a singing voice in …
singing voice in polyphonic music, and the other is estimating the pitch of a singing voice in …
Adversarial semi-supervised audio source separation applied to singing voice extraction
The state of the art in music source separation employs neural networks trained in a
supervised fashion on multi-track databases to estimate the sources from a given mixture …
supervised fashion on multi-track databases to estimate the sources from a given mixture …