# ZeyueT/AudioX

[ICLR 2026] Repository of AudioX

Repository: https://github.com/ZeyueT/AudioX
Canonical: https://ross.abutalabs.com/products/audiox
Homepage: https://zeyuet.github.io/AudioX/
Language: Python
License: NOASSERTION
License Family: other
Last push: 2026-03-10T14:09:01+00:00

## Health v2 (maintenance only)
Score: 52/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 71, release rhythm 35, longevity 38
- inputs: {"age_days": 538, "days_push": 176, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1552, forks 142 (observed 2026-08-28T04:05:02.324780+00:00)

## What it is
AudioX is a unified multimodal framework for anything-to-audio generation, producing audio and music conditioned on text, video, image, or audio inputs via a Multimodal Adaptive Fusion module. It is the official research code release for an ICLR 2026 paper, trained on the large-scale IF-caps dataset of over 7 million samples.

## Use cases
- generate sound effects from a text prompt
- create music from a text description
- generate audio for a silent video
- complete or inpaint missing audio segments
- research multimodal-conditioned audio generation models
- benchmark text-to-audio and text-to-music generation

## When to choose
- you need a single model that handles text-to-audio, text-to-music, video-to-audio, and audio inpainting
- you want a state-of-the-art research model with pretrained checkpoints on Hugging Face
- you have a CUDA-capable GPU and want to experiment with multimodal audio generation

## When to avoid
- you need production-grade audio synthesis with commercial licensing guarantees (license is not standard)
- you have no GPU and need fast, lightweight audio generation
- you need real-time or low-latency audio synthesis

## Facets
- artifact type: library
- maturity: active
- function: machine-learning, deep-learning, audio-processing, llm-inference
- domain: artificial-intelligence, machine-learning, deep-learning
- platform: python
- tags: audio-generation, text-to-audio, text-to-music, video-to-audio, diffusion, multimodal, iclr-2026, research, audio, gpu, linux

## Member repositories
- ZeyueT/AudioX (main) score 52

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:02.324780+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:30:11.462083+00:00, confidence not recorded.
  - readme: https://github.com/ZeyueT/AudioX (fetched 2026-08-28T04:05:02.324780+00:00, sha 549e5870b17c)
  - homepage: https://zeyuet.github.io/AudioX/ (fetched 2026-08-29T11:30:34.885213+00:00, sha ab026aed4dfb)
- Data as of 2026-08-30T08:39:29.467469+00:00.