论文标题
相对声学特征，用于智能级别的距离估计
Relative Acoustic Features for Distance Estimation in Smart-Homes
论文作者
论文摘要
任何音频记录都封装了相关声学环境的独特指纹，即背景噪声和混响。考虑到配备了一个或多个麦克风和可穿戴智能设备（手表，眼镜或智能手机）的固定智能扬声器设备的房间的情况，我们采用了改进的比例归一化的均等最小平方自适应过滤器，以估计相对房间的冲动响应映射了这两个设备的音频记录。我们通过利用一组新的功能来进行设备间距离估计，从而将房间脉冲响应的某些声学属性的定义扩展到其相对版本。结合估计的相对室内脉冲响应的稀疏度度量，相对特征允许精确的设备间距离估计，可以利用该任务，例如最佳麦克风选择或声学场景分析。来自不同维度和混响时间的模拟房间的实验结果证明了这种计算轻量级方法在智能家庭声学范围内应用的有效性
Any audio recording encapsulates the unique fingerprint of the associated acoustic environment, namely the background noise and reverberation. Considering the scenario of a room equipped with a fixed smart speaker device with one or more microphones and a wearable smart device (watch, glasses or smartphone), we employed the improved proportionate normalized least mean square adaptive filter to estimate the relative room impulse response mapping the audio recordings of the two devices. We performed inter-device distance estimation by exploiting a new set of features obtained extending the definition of some acoustic attributes of the room impulse response to its relative version. In combination with the sparseness measure of the estimated relative room impulse response, the relative features allow precise inter-device distance estimation which can be exploited for tasks such as best microphone selection or acoustic scene analysis. Experimental results from simulated rooms of different dimensions and reverberation times demonstrate the effectiveness of this computationally lightweight approach for smart home acoustic ranging applications
