Paper ID: 2410.05739

Array2BR: An End-to-End Noise-immune Binaural Audio Synthesis from Microphone-array Signals

Cheng Chi, Xiaoyu Li, Andong Li, Yuxuan Ke, Xiaodong Li, Chengshi Zheng

Telepresence technology aims to provide an immersive virtual presence for remote conference applications, and it is extremely important to synthesize high-quality binaural audio signals for this aim. Because the ambient noise is often inevitable in practical application scenarios, it is highly desired that binaural audio signals without noise can be obtained from microphone-array signals directly. For this purpose, this paper proposes a new end-to-end noise-immune binaural audio synthesis framework from microphone-array signals, abbreviated as Array2BR, and experimental results show that binaural cues can be correctly mapped and noise can be well suppressed simultaneously using the proposed framework. Compared with existing methods, the proposed method achieved better performance in terms of both objective and subjective metric scores.

Submitted: Oct 8, 2024