Audio-based musical version identification: Elements and challenges
Creating novel interpretations of existing musical compositions is and has always been an
essential part of musical practice. Before the advent of recorded music, listening to a piece of …
essential part of musical practice. Before the advent of recorded music, listening to a piece of …
Bytecover: Cover song identification via multi-loss training
We present in this paper ByteCover, which is a new feature learning method for cover song
identification (CSI). Byte-Cover is built based on the classical ResNet model, and two major …
identification (CSI). Byte-Cover is built based on the classical ResNet model, and two major …
Artist similarity with graph neural networks
Artist similarity plays an important role in organizing, understanding, and subsequently,
facilitating discovery in large collections of music. In this paper, we present a hybrid …
facilitating discovery in large collections of music. In this paper, we present a hybrid …
Training deep pitch-class representations with a multi-label CTC loss
Despite the success of end-to-end approaches, chroma (or pitch-class) features remain a
useful mid-level representation of music audio recordings due to their direct interpretability …
useful mid-level representation of music audio recordings due to their direct interpretability …
Deep learning for audio and music
This chapter provides an overview of how deep learning techniques can be used for audio
signals. We first review the main DNN architectures, meta-architectures and training …
signals. We first review the main DNN architectures, meta-architectures and training …
[PDF][PDF] Artist Similarity for Everyone: A Graph Neural Network Approach.
F Korzeniowski, S Oramas… - Trans. Int. Soc. Music. Inf …, 2022 - scholar.archive.org
Artist similarity plays an important role in organizing, understanding, and subsequently,
facilitating discovery in large collections of music. In this paper, we present a hybrid …
facilitating discovery in large collections of music. In this paper, we present a hybrid …
Assessing algorithmic biases for musical version identification
Version identification (VI) systems now offer accurate and scalable solutions for detecting
different renditions of a musical composition, allowing the use of these systems in industrial …
different renditions of a musical composition, allowing the use of these systems in industrial …
The deep learning revolution in mir: The pros and cons, the needs and the challenges
G Peeters - International Symposium on Computer Music …, 2019 - Springer
This paper deals with the deep learning revolution in Music Information Research (MIR), ie
the switch from knowledge-driven hand-crafted systems to data-driven deep-learning …
the switch from knowledge-driven hand-crafted systems to data-driven deep-learning …
And what if two musical versions don't share melody, harmony, rhythm, or lyrics?
M Abrassart, G Doras - ISMIR 2022, 2022 - hal.science
Version identification (VI) has seen substantial progress over the past few years. On the one
hand, the introduction of the metric learning paradigm has favored the emergence of …
hand, the introduction of the metric learning paradigm has favored the emergence of …
Pairwise similarity normalization based on a hubness score for improving cover song retrieval accuracy
JS Seo - IEICE TRANSACTIONS on Information and Systems, 2022 - search.ieice.org
A hubness-score based normalization of the pairwise similarity is proposed for the sequence-
alignment based cover song retrieval. The hubness, which is the tendency of some data …
alignment based cover song retrieval. The hubness, which is the tendency of some data …