In the field of music information retrieval (MIR), cover song identification (CSI) is a
challenging task that aims to identify cover versions of a query song from a massive …

Cover song identification is an important problem in the field of Music Information Retrieval.
Most existing methods rely on hand-crafted features and sequence alignment methods, and …

Cover song identification is a challenging task in the field of Music Information Retrieval
(MIR) due to complex musical variations between query tracks and cover versions. Previous …

Cross-version music retrieval aims at identifying all versions of a given piece of music using
a short query audio fragment. One previous approach, which is particularly suited for …

Many applications utilize sensors on mobile devices and apply deep learning for diverse
applications. However, they have rarely enjoyed mainstream adoption due to many different …

In recent years, several deep learning models have been proposed for cover song
identification and they have been designed to learn fixed-length feature vectors for music …

In this paper, we propose a cover song identification algorithm using a convolutional neural
network (CNN). We first train the CNN model to classify any non-/cover relationship, by …

Cover song detection is a very relevant task in Music Information Retrieval (MIR) studies and
has been mainly addressed using audio-based systems. Despite its potential impact in …

Birdsong detection with machine learning (ML) models can provide valuable insights for
informed decision making in conservation efforts. Previous methods usually convert audio to …

This paper studies the novel problem of automatic live music song identification, where the
goal is, given a live recording of a song, to retrieve the corresponding studio version of the …