Combining global and local text embeddings in a diffusion UNet for music improves text adherence, while mean-pooling T5 local embeddings yields the best audio quality without extra parameters.
AudioLDM: Text-to-audio generation with latent diffusion models,
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Diffusion based Text-to-Music Generation with Global and Local Text based Conditioning
Combining global and local text embeddings in a diffusion UNet for music improves text adherence, while mean-pooling T5 local embeddings yields the best audio quality without extra parameters.