Ambisonizer: Neural Upmixing as Spherical Harmonics Generation

Fuente: arXiv
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Autori principali: Zang, Yongyi, Wang, Yifan, Lee, Minglun
Natura: Preprint
Pubblicazione: 2024
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author Zang, Yongyi
Wang, Yifan
Lee, Minglun
author_facet Zang, Yongyi
Wang, Yifan
Lee, Minglun
contents Neural upmixing, the task of generating immersive music with an increased number of channels from fewer input channels, has been an active research area, with mono-to-stereo and stereo-to-surround upmixing treated as separate problems. In this paper, we propose a unified approach to neural upmixing by formulating it as spherical harmonics - more specifically, Ambisonic generation. We explicitly formulate mono upmixing as unconditional generation and stereo upmixing as conditional generation, where the stereo signals serve as conditions. We provide evidence that our proposed methodology, when decoded to stereo, matches a strong commercial stereo widener in subjective ratings. Overall, our work presents direct upmixing to Ambisonic format as a strong and promising approach to neural upmixing. A discussion on limitations is also provided.
format Preprint
id arxiv_https___arxiv_org_abs_2405_13428
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Ambisonizer: Neural Upmixing as Spherical Harmonics Generation
Zang, Yongyi
Wang, Yifan
Lee, Minglun
Sound
Audio and Speech Processing
Neural upmixing, the task of generating immersive music with an increased number of channels from fewer input channels, has been an active research area, with mono-to-stereo and stereo-to-surround upmixing treated as separate problems. In this paper, we propose a unified approach to neural upmixing by formulating it as spherical harmonics - more specifically, Ambisonic generation. We explicitly formulate mono upmixing as unconditional generation and stereo upmixing as conditional generation, where the stereo signals serve as conditions. We provide evidence that our proposed methodology, when decoded to stereo, matches a strong commercial stereo widener in subjective ratings. Overall, our work presents direct upmixing to Ambisonic format as a strong and promising approach to neural upmixing. A discussion on limitations is also provided.
title Ambisonizer: Neural Upmixing as Spherical Harmonics Generation
topic Sound
Audio and Speech Processing
url https://arxiv.org/abs/2405.13428