方向保持主动噪声控制与条件控制滤波器估计网络
Direction-Preserving Active Noise Control with a Conditional Control-Filter Estimation Network
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中文总结 AI 辅助
本文提出一种基于条件控制滤波器估计网络的方向保持主动噪声控制方法，通过方向条件化优化和FiLM卷积网络实现噪声衰减与期望信号保留的权衡，在3300余案例中实现22.8 dB降噪。
中文摘要 AI 辅助
传统主动噪声控制（ANC）在误差麦克风处最小化总扰动，而不区分期望声音与噪声。方向保持主动噪声控制（DP-ANC）旨在衰减来自指定期望方向以外的噪声分量，同时保留自然来自该方向的声音。现有方法通常要么需要对每个新观测重复进行解析优化，要么通过透听次级源路径估计并重现期望分量。为解决这些局限性，本文将DP-ANC表述为方向条件化的消除-保留优化问题。一个分量分离的目标函数联合惩罚残余噪声能量和由期望分量引起的控制响应，并通过标量权重参数控制消除-保留权衡。一个通过特征级线性调制（FiLM）以指定期望方向为条件的卷积网络，使用可微分的次级路径感知前向模型进行训练。在部署时，网络直接从混合参考观测和指定期望方向，在单次前向传播中估计完整的多通道有限脉冲响应（FIR）控制滤波器组，同时保留传统前馈ANC信号路径。在超过3300个评估案例中，所选工作点实现了22.8 dB的平均噪声降低，期望信号失真为-11.4 dB。使用实测入耳式设备传递函数的验证进一步表明，在实测声学配置下性能一致。
英文摘要
Conventional active noise control (ANC) minimizes the total disturbance at the error microphone without distinguishing desired sound from noise. Direction-preserving ANC (DP-ANC) instead aims to attenuate a noise component arriving from a direction other than the specified desired direction while preserving sound naturally arriving from that direction. Existing approaches typically either require analytical optimization to be repeated for each new observation or estimate and reproduce the desired component through a hear-through secondary-source path. To address these limitations, this paper formulates DP-ANC as a direction-conditioned cancellation-preservation optimization problem. A component-separated objective jointly penalizes residual noise energy and the control response induced by the desired component, with a scalar weighting parameter controlling the cancellation-preservation trade-off. A convolutional network conditioned on the specified desired direction through feature-wise linear modulation (FiLM) is trained using a differentiable secondary-path-aware forward model. At deployment, the network estimates the complete multichannel finite impulse response (FIR) control-filter bank directly from a mixed-reference observation and the specified desired direction in a single forward pass, while retaining the conventional feedforward ANC signal path. Over 3300 evaluation cases, the selected operating point achieves 22.8 dB mean noise reduction with a desired-signal distortion of -11.4 dB. Validation using measured in-ear-device transfer functions further demonstrates consistent performance under measured acoustic configurations.
