Introduction
AudioLDM applies latent diffusion to general sound synthesis through language–audio representations, extending the research timeline to environmental audio and sound editing.
View full image ↗Figure 1: the original AudioLDM diagram of training, text-conditioned sampling and audio editing. Source: v3; the image version is distinct from the initial submission date.
Liu, Haohe; Chen, Zehua; Yuan, Yi; Mei, Xinhao; Liu, Xubo; Mandic, Danilo; Wang, Wenwu; Plumbley, Mark D. · original paper / arXiv · Rights in the paper and depicted works remain with their holders. Research quotation does not establish an open licence; republication rights await independent review.
Source · AudioLDM: Text-to-Audio Generation with Latent Diffusion Models ↗RESEARCH ACCOUNT
AudioLDM applies latent diffusion to general sound synthesis through language–audio representations, extending the research timeline to environmental audio and sound editing.
ANTI-AI ARCHIVE · Revised 2026-10-03
What the paper investigates
The system uses aligned CLAP representations, training with audio embeddings and conditioning sampling with text embeddings. Its demonstrations also explore audio manipulation, showing that sound generation involves its own representations and transformations rather than merely changing an image model’s output label.
Section sources: AudioLDM: Text-to-Audio Generation with Latent Diffusion Models
Its place in generative-art history
Editorial interpretation: text becomes an input for organising sonic environments, bringing timbre, events and imagined spaces into generative production. Author-hosted audio examples remain essential because a static diagram cannot communicate the resulting sound.
Section sources: AudioLDM: Text-to-Audio Generation with Latent Diffusion Models
Reading limits and versions
General sound synthesis differs from generating musical structure. Objective and listening evaluations do not determine artistic value.
Section sources: AudioLDM: Text-to-Audio Generation with Latent Diffusion Models
Sources for this account
Read the arXiv abstract, authors and version history, plus the selected figure/page on PDF page 2; proofs and full experiments were not independently audited.
Read the arXiv abstract, authors and version history, plus the selected figure/page on PDF page 2; proofs and full experiments were not independently audited. The account and translation are AI-assisted, pending independent human review. Section references identify evidence without claiming independent verification of every historical statement.
Continue with a comparative question
AudioLDM: compare methods, control or evaluation conditions with MusicGen.
AudioLDM: compare methods, control or evaluation conditions with Jukebox.
AudioLDM: compare methods, control or evaluation conditions with Fair music-AI licensing.
Dates & version record
Date displayed for this node: 2023-01-29 · Historical date recorded for the source: 2023-01-29
The timeline uses the initial arXiv submission, distinct from conference publication, model release and the archive addition on 3 October 2026. The account and image refer to v3; its date is recorded in the source history.
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Original sources & further reading
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AudioLDM: Text-to-Audio Generation with Latent Diffusion Models
https://arxiv.org/abs/2301.12503
Current cited URL
Read the arXiv abstract, authors and version history, plus the selected figure/page on PDF page 2; proofs and full experiments were not independently audited.
Provenance, translation & verification
Archive node #213 · Initial research-paper submission; methods, evaluation and production conditions
Research materials & supplement references · 1
Recent research papers: additions and reconciled sources since 2022 · Read the arXiv abstract, authors and version history, plus the selected figure/page on PDF page 2; proofs and full experiments were not independently audited. · 012
Date as recorded: 2023-01-29
AudioLDM: Text-to-Audio Generation with Latent Diffusion Models ↗
AudioLDM: Text-to-Audio Generation with Latent Diffusion Models
Archive account based on the listed research materials, not a full translation of the linked work. AI-assisted translation; independent human review pending.
Official material was read within the stated scope; see the source note for reading limits and outstanding checks.
Cite this node
ANTI-AI ARCHIVE. AudioLDM: Text-to-Audio Generation with Latent Diffusion Models. Art-history node #213. https://salondesrefuses.cn/en/art-history/335
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