Music emotion recognition (MER) field rapidly expanded in the last decade. Many new
methods and new audio features are developed to improve the performance of MER …

One of the major reasons why people find music so enjoyable is its emotional impact.
Creating emotion-based playlists is a natural way of organizing music. The usability of …

Current music emotion recognition (MER) systems rely on emotion data averaged across
listeners and over time to infer the emotion expressed by a musical piece, often neglecting …

Musical features and descriptors could be coarsely divided into three levels of complexity.
The bottom level contains the basic building blocks of music, eg, chords, beats and timbre …

This paper presents a new multimodal dataset Moodo that can aid the development of
affective music information retrieval systems. Moodo's main novelties are a multimodal …

The subjectivity of listeners' emotional responses to music is at the crux of optimizing
emotion-aware music recommendation. To address this challenge, we constructed a new …

This book presents the most important issues with automated systems for music emotion
recognition. These problems include emotion representation, annotation of music excerpts …

In this work, we present a novel method for music emotion recognition that leverages Large
Language Model (LLM) embeddings for label alignment across multiple datasets and zero …

Purpose–The purpose of this paper is to explore how both producers and consumers of user-
created music videos on YouTube communicate emotional information …

The paper presents an original approach to music emotion recognition. We propose to use
recurrent neural networks to separate the representation learning process from the classifier …