Multi-modal music generation, using multiple modalities like images, video, and text alongside musical scores and audio as guidance, is an emerging research area with broad applications. This paper reviews this field, categorizing music generation systems from the perspective of modalities. It covers modality representation, multi-modal data alignment, and their utilization to guide music generation. We also discuss current datasets and evaluation methods. Key challenges in this area include effective multi-modal integration, large-scale comprehensive datasets, and systematic evaluation methods. Finally, we provide an outlook on future research directions focusing on multi-modal fusion, alignment, data, and evaluation.
View on arXiv@article{li2025_2504.00837,
title={ A Survey on Music Generation from Single-Modal, Cross-Modal, and Multi-Modal Perspectives: Data, Methods, and Challenges },
author={ Shuyu Li and Shulei Ji and Zihao Wang and Songruoyao Wu and Jiaxing Yu and Kejun Zhang },
journal={arXiv preprint arXiv:2504.00837},
year={ 2025 }
}