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 2: Learning holistic audio generation with self-supervised pretraining,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
baseline 1
citation-polarity summary
fields
eess.AS 1years
2025 1verdicts
CONDITIONAL 1roles
baseline 1polarities
baseline 1representative citing papers
citing papers explorer
-
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.