用输出质量选麦克风参数，让助听器在嘈杂环境更清晰
Listen first: Output-based multi-microphone speech enhancement
- 根据输出信号质量动态选择最佳波束成形器
- 低信噪比下语音质量提升显著，各项指标均优于传统方法
- 适合需要强抗干扰能力的助听设备研发者
传统助听器语音增强算法依赖输入信号特征（如语音活动检测）配置波束成形器，但在复杂声学环境下噪声信号特征不可靠。本文提出新范式：通过评估输出信号特性来决定系统参数。实验采用输出驱动的最小功率无失真响应（MPDR）波束成形器集合进行选择。尽管MPDR对指向误差敏感，但在输出驱动框架下表现有效。与传统的输入驱动最小方差无失真响应（MVDR）基线相比，所提系统在低信噪比条件下持续表现更优，各项指标（SNR、ESTOI、PESQ）均显著提升。
原文摘要 · Abstract (English)
Traditionally, hearing-aid speech enhancement (SE) algorithms rely on input-based feature estimation, often derived by a voice activity detector (VAD), to configure beamformers. Yet features extracted from noisy microphone signals can become unreliable in challenging acoustic scenes where users most need help. We introduce a novel paradigm in which the settings of a sound processing system are determined by evaluating characteristics of its output. To demonstrate this idea, we employ an output-based system that selects among a set of minimum power distortionless response (MPDR) beamformers. Although MPDR beamformers are typically avoided due to their sensitivity to steering errors, we show that they become effective within an output-based framework. We compare the proposed system to a conventional input-based minimum variance distortionless response (MVDR) baseline. Experimental results show that the proposed system consistently outperforms the MVDR baseline, particularly at low SNRs, in terms of SNR, ESTOI and PESQ.
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