提出轻量级端到端双耳语音定位模型，提升嘈杂环境中的声源定位精度。
Binaural Localization Model for Speech in Noise
- 采用轻量卷积循环网络处理双耳噪声混响信号
- 在真实听觉阈值下实现前向方位角精确定位
- 可评估双耳语音增强方法的线索保留效果
双耳声源定位对人类的空间感知、沟通与安全至关重要。本文提出一种面向噪声环境的端到端双耳定位模型，采用轻量级卷积循环网络，对前方方位角平面内的噪声混响双耳信号进行定位。模型引入内耳加性噪声以模拟典型听者的频率依赖性听觉阈值。通过对比波束成形响应功率算法，评估了该模型的定位性能，并研究其作为双耳语音增强方法中双耳线索保留度量的适用性。还进行了听觉实验，比较该模型与人类在嘈杂条件下对语音定位的表现。
原文摘要 · Abstract (English)
Binaural acoustic source localization is important to human listeners for spatial awareness, communication and safety. In this paper, an end-to-end binaural localization model for speech in noise is presented. A lightweight convolutional recurrent network that localizes sound in the frontal azimuthal plane for noisy reverberant binaural signals is introduced. The model incorporates additive internal ear noise to represent the frequency-dependent hearing threshold of a typical listener. The localization performance of the model is compared with the steered response power algorithm, and the use of the model as a measure of interaural cue preservation for binaural speech enhancement methods is studied. A listening test was performed to compare the performance of the model with human localization of speech in noisy conditions.
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