TEAdapter: Supply abundant guidance for controllable text-to-music generation
<|reference_start|>TEAdapter: Supply abundant guidance for controllable text-to-music generation: Although current text-guided music generation technology can cope with simple creative scenarios, achieving fine-grained control over individual text-modality conditions remains challenging as user demands become more intricate. Accordingly, we introduce the TEAcher Adapter (TEAdapter), a compact plugin designed to guide the generation process with diverse control information provided by users. In addition, we explore the controllable generation of extended music by leveraging TEAdapter control groups trained on data of distinct structural functionalities. In general, we consider controls over global, elemental, and structural levels. Experimental results demonstrate that the proposed TEAdapter enables multiple precise controls and ensures high-quality music generation. Our module is also lightweight and transferable to any diffusion model architecture. Available code and demos will be found soon at https://github.com/Ashley1101/TEAdapter.<|reference_end|>
@article{zou2024teadapter:,
    title={TEAdapter: Supply abundant guidance for controllable text-to-music
  generation},
    author={Jialing Zou, Jiahao Mei, Xudong Nan, Jinghua Li, Daoguo Dong, Liang He},
    journal={2024 IEEE International Conference on Multimedia and Expo (ICME
  2024)},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.04865},
    primaryClass={cs.SD cs.MM eess.AS}
}