Music Emotion Dataset with 2496 Songs for Music Emotion Recognition (Memo2496)

Music emotion recognition delineates and categorises the spectrum of emotions expressed within musical compositions by conducting a comprehensive analysis of fundamental attributes, including melody, rhythm, and timbre. This task is pivotal for the tailoring of music recommendations, the enhancement of music production, the facilitation of psychotherapeutic interventions, and the execution of market analyses, among other applications. The cornerstone is the establishment of a music emotion recognition dataset annotated with reliable emotional labels, furnishing machine learning algorithms with essential training and validation tools, thereby underpinning the precision and dependability of emotion detection. The Music Emotion Dataset with 2496 Songs (Memo2496) dataset, comprising 2496 instrumental musical pieces annotated with valence-arousal (VA) labels and acoustic features, is introduced to advance music emotion recognition and affective computing. The dataset is meticulously annotated by 30 music experts proficient in music theory and devoid of cognitive impairments, ensuring an unbiased perspective. The annotation methodology and experimental paradigm are grounded in previously validated studies, guaranteeing the integrity and high calibre of the data annotations.

Memo2496 R1 updated by Qilin Li @12Feb2025

1. Remove some unannotated music raw data, now the music contained in MusicRawData.zip file are all annotated music.

2. The ‘Music Raw Data.zip’ file on FigShare has been updated to contain 2496 songs, consistent with the corpus described in the manuscript. The metadata fields on “Title”, “Contributing Artists”, “Genre”, and/or “Album” have been removed to ensure the songs remain anonymous.

3. Adjusted the file structure, now the files on FigShare are placed in folders named ‘Music Raw Data’, ‘Annotations’, ‘Features’, and ‘Data Processing Utilities’ to reflect the format of the Data Records section in the manuscript.

Memo2496 R2 updated by Qilin Li @14Feb2025

The source of each song's download platform has been added in ‘songs_info_all.csv’ to enable users to search within the platform itself if necessary. This approach aims to balance the privacy requirements of the data with the potential needs of the dataset's users.