A binaural rendering framework for personal sound zones (PSZs) is proposed to enable multiple head-tracked listeners to receive fully independent stereo audio programs. Current PSZ systems typically rely on monophonic rendering and therefore cannot control the left and right ears separately, which limits the quality and accuracy of spatial imaging. The proposed method employs a Binaural Spatially Adaptive Neural Network (BSANN) to generate ear-optimized loudspeaker filters that reconstruct the desired acoustic field at each ear of multiple listeners. The framework integrates anechoically measured loudspeaker frequency responses, analytically modeled transducer directivity, and rigid-sphere head-related transfer functions (HRTFs) to enhance acoustic accuracy and spatial rendering fidelity. An explicit active crosstalk cancellation (XTC) stage further improves three-dimensional spatial perception. Experiments show significant gains in measured objective performance metrics, including inter-zone isolation (IZI), inter-program isolation (IPI), and crosstalk cancellation (XTC), with log-frequency-weighted values of 10.23/10.03 dB (IZI), 11.11/9.16 dB (IPI), and 10.55/11.13 dB (XTC), respectively, over 100-20,000 Hz. The combined use of ear-wise control, accurate acoustic modeling, and integrated active XTC produces a unified rendering method that delivers greater isolation performance, increased robustness to room asymmetry, and more faithful spatial reproduction in real acoustic environments.

翻译：本文提出了一种用于个人声区（PSZ）的双耳渲染框架，旨在使多个头部被追踪的听众能够接收完全独立的立体声音频节目。当前的PSZ系统通常依赖于单声道渲染，因此无法分别控制左右耳，这限制了空间成像的质量与精度。所提出的方法采用双耳空间自适应神经网络（BSANN）来生成针对耳朵优化的扬声器滤波器，以重建多位听众每只耳朵处期望的声场。该框架集成了消声室测量的扬声器频率响应、解析建模的换能器指向性以及刚性球头相关传递函数（HRTF），以提升声学精度与空间渲染保真度。一个显式的主动串扰消除（XTC）阶段进一步改善了三维空间感知。实验显示，在100-20,000 Hz频率范围内，测得的客观性能指标均有显著提升，包括区间隔离度（IZI）、节目间隔离度（IPI）和串扰消除（XTC），其对数频率加权值分别为10.23/10.03 dB（IZI）、11.11/9.16 dB（IPI）和10.55/11.13 dB（XTC）。通过结合使用分耳控制、精确声学建模以及集成的主动XTC技术，该方法形成了一种统一的渲染方案，能够在真实声学环境中实现更高的隔离性能、对房间不对称性更强的鲁棒性以及更准确的空间重放。