# SRC-gAudio: Sampling-Rate-Controlled Audio Generation

arXiv: https://arxiv.org/abs/2410.06544 · HTML: https://mlsanity.com/paper/2410.06544/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Oct 2024.

## Built on by (most cited first, 1 of 1)

- [AI-Based Sound Effect Generation: A Narrative Review of Generative Models Across Input Modalities](https://mlsanity.com/paper/2608.03742/) (2026)

## Abstract (arXiv)

We introduce SRC-gAudio, a novel audio generation model designed to facilitate text-to-audio generation across a wide range of sampling rates within a single model architecture. SRC-gAudio incorporates the sampling rate as part of the generation condition to guide the diffusion-based audio generation process. Our model enables the generation of audio at multiple sampling rates with a single unified model. Furthermore, we explore the potential benefits of large-scale, low-sampling-rate data in enhancing the generation quality of high-sampling-rate audio. Through extensive experiments, we demonstrate that SRC-gAudio effectively generates audio under controlled sampling rates. Additionally, our results indicate that pre-training on low-sampling-rate data can lead to significant improvements in audio quality across various metrics.