提出新损失函数，让助听器更好保留声音方向感。
A Novel Binaural Cue Preservation Loss for DNN-Based Binaural Speech Enhancement
- 设计双耳线索保持损失，直接优化左右耳信号关系
- 相比现有方法，降低掩蔽导致的双耳失真，提升方向感保真度
- 适合关注听觉空间感知的语音增强研究者
助听器中的双耳语音增强旨在降噪的同时保留用于声源定位的双耳线索。尽管基于深度神经网络的方法能实现强降噪效果，但常会扭曲左右信号间的关系。本文提出两种新型双耳线索保持损失：第一种是双耳重建误差损失，直接惩罚由掩蔽引起的左右频谱关系失真，比以往分别计算双耳强度差（ILD）和双耳相位差（IPD）误差的方式更直接地衡量双耳一致性；第二种是联合建模ILD与IPD的双耳线索损失，以更好地保持双耳结构。实验结果表明，两种损失均在保持强降噪性能的同时，显著降低掩蔽引起的失真，优于当前最先进的基线线索损失。其中，第二种联合损失在ILD保持方面也优于基线。
原文摘要 · Abstract (English)
Binaural speech enhancement for hearing aids aims to reduce noise while preserving the interaural cues needed for spatial localization. Although deep neural network-based methods achieve strong noise reduction, they often distort the rela- tionship between the left and right signals. In this paper, we propose two novel binaural cue preservation losses. First, a binaural reconstruction error loss that directly penalizes masking-induced distortion in the relationship between the left and right spectra, providing a more direct measure of the binaural consistency than conventional separate interaural level differences (ILD) and interaural phase differences (IPD) errors as in prior work. Second, a binaural cue loss that jointly models ILD and IPD to better preserve the binaural structure. Experimental results show that both proposed losses maintain strong noise reduction performance and reduce masking- induced distortion compared to the state-of-the-art baseline cue loss, while the second proposed joint binaural cue loss also outperforms the baseline in ILD preservation.
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