# PPPR: Portable Plug-in Prompt Refiner for Text to Audio Generation

arXiv: https://arxiv.org/abs/2406.04683 · HTML: https://mlsanity.com/paper/2406.04683/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 7 Jun 2024.

## Built on by (most cited first, 2 of 2)

- [TA-V2A: Textually Assisted Video-to-Audio Generation](https://mlsanity.com/paper/2503.10700/) (2025)
- [InstructAudio: Unified speech and music generation with natural language instruction](https://mlsanity.com/paper/2511.18487/) (2025)

## Abstract (arXiv)

Text-to-Audio (TTA) aims to generate audio that corresponds to the given text description, playing a crucial role in media production. The text descriptions in TTA datasets lack rich variations and diversity, resulting in a drop in TTA model performance when faced with complex text. To address this issue, we propose a method called Portable Plug-in Prompt Refiner, which utilizes rich knowledge about textual descriptions inherent in large language models to effectively enhance the robustness of TTA acoustic models without altering the acoustic training set. Furthermore, a Chain-of-Thought that mimics human verification is introduced to enhance the accuracy of audio descriptions, thereby improving the accuracy of generated content in practical applications. The experiments show that our method achieves a state-of-the-art Inception Score (IS) of 8.72, surpassing AudioGen, AudioLDM and Tango.