[R] WavJourney: Compositional Audio Creation with Large Language Models - University of Surrey 2023

Paper: [https://arxiv.org/abs/2307.14335](https://arxiv.org/abs/2307.14335)

Github: [https://github.com/Audio-AGI/WavJourney](https://github.com/Audio-AGI/WavJourney)

Project Page: [https://audio-agi.github.io/WavJourney\_demopage/](https://audio-agi.github.io/WavJourney_demopage/)

Demo: [https://huggingface.co/spaces/Audio-AGI/WavJourney](https://huggingface.co/spaces/Audio-AGI/WavJourney)

Abstract:

>Large Language Models (LLMs) have shown great promise in integrating diverse expert models to tackle intricate language and vision tasks. Despite their significance in advancing the field of Artificial Intelligence Generated Content (AIGC), their potential in intelligent audio content creation remains unexplored. In this work, we tackle the problem of creating audio content with storylines encompassing speech, music, and sound effects, guided by text instructions. We present WavJourney, a system …

abstract aigc artificial artificial intelligence audio diverse expert generated intelligence intelligent language language models large language large language models llms machinelearning music significance speech tasks vision work