Text-to-Audio Generation using Instruction-Tuned LLM and Latent Diffusion Model

research work·research paper·active

Research work examining audio generation, text-to-audio generation.

Recorded facts

Official site	https://arxiv.org/abs/2304.13731 ↗
Geography	Global
arxiv	2304.13731
venue	https://github.com/declare-lab/tango
authors	Deepanway Ghosal; Navonil Majumder; Ambuj Mehrish; Soujanya Poria
methods	diffusion modeling; language modeling
code urls	https://github.com/declare-lab/tango
demo urls	unknown
exact title	Text-to-Audio Generation using Instruction-Tuned LLM and Latent Diffusion Model
project urls	unknown
original title	unknown
citation counts	unknown
research topics	audio generation; text-to-audio generation
peer review status	not established from abstract metadata
disclosed conflicts	unknown
stated contribution	Presents or evaluates the system, method, benchmark, or analysis identified in the paper title.
us market scope basis	Included as a materially relevant public research artifact in the US-facing AI-music ecosystem; direct affiliation varies.
funding acknowledgements	unknown
affiliations at publication	unknown
publication or preprint date	2023-04-24
abstract level neutral summary	The work studies audio generation, text-to-audio generation; methods and evaluation details are in the official abstract.
datasets benchmarks models tools used	AudioCaps; AudioLDM
correction withdrawal retraction status	No withdrawal marker observed in captured arXiv metadata.