arxiv:2011.11970

A Novel Multimodal Music Genre Classifier using Hierarchical Attention and Convolutional Neural Network

Published on Nov 24, 2020

Authors:

Abhilash Nandy

Abstract

A CNN and Hierarchical Attention Network are used to extract acoustic and textual features, respectively, for classifying music genre.

AI-generated summary

Music genre classification is one of the trending topics in regards to the current Music Information Retrieval (MIR) Research. Since, the dependency of genre is not only limited to the audio profile, we also make use of textual content provided as lyrics of the corresponding song. We implemented a CNN based feature extractor for spectrograms in order to incorporate the acoustic features and a Hierarchical Attention Network based feature extractor for lyrics. We then go on to classify the music track based upon the resulting fused feature vector.

View arXiv page View PDF Add to collection

Community

Upload images, audio, and videos by dragging in the text input, pasting, or clicking here.

Tap or paste here to upload images

· Sign up or log in to comment

Upvote

Models citing this paper 0

No model linking this paper

Cite arxiv.org/abs/2011.11970 in a model README.md to link it from this page.

Datasets citing this paper 0

No dataset linking this paper

Cite arxiv.org/abs/2011.11970 in a dataset README.md to link it from this page.

Spaces citing this paper 0

No Space linking this paper

Cite arxiv.org/abs/2011.11970 in a Space README.md to link it from this page.

Collections including this paper 0

No Collection including this paper

Add this paper to a collection to link it from this page.