Classification and study of music genres with multimodal Spectro-Lyrical Embeddings for Music (SLEM)

The essence of music is inherently multi-modal – with audio and lyrics going hand in hand. However, there is very less research done to study the intricacies of the multi-modal nature of music, and its relation with genres. Our work uses this multi-modality to present spectro-lyrical embeddings for...

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Veröffentlicht in:	Multimedia tools and applications Jg. 84; H. 7; S. 3701 - 3721
Hauptverfasser:	Mehra, Ashman, Mehra, Aryan, Narang, Pratik
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.02.2025 Springer Nature B.V
Schlagworte:	Algorithms Classification Clustering Computer Communication Networks Computer Science Data Structures and Information Theory Deep learning Genre Machine learning Multimedia Information Systems Music Special Purpose and Application-Based Systems Spectrograms Representation learning Multimodal music embeddings Music Spectrograms Machine learning
ISSN:	1573-7721, 1380-7501, 1573-7721
Online-Zugang:	Volltext
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