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
翻译:任何音频录音都封封封相关声响环境的独特指纹,即背景噪音和反响。考虑到配备固定的智能扬声器、一个或多个麦克风和可磨损智能装置(手表、眼镜或智能耳机)的房间的情况,我们采用了经过改进的按比例平准最小平方适应过滤器,以估计相对室的脉冲反应反应,测绘两个装置的录音记录。我们利用获得的一套新特征,将室内脉冲反应的某些声学特性定义扩展至相对版本,从而进行了跨点距离估计。结合估计相对室脉冲反应的稀疏度测量,相对特征使得能够精确地进行跨点距离估计,用于最佳麦克声选择或声场分析等任务。不同尺寸的模拟室的实验结果和回响时间证明了智能家庭声谱应用的计算轻度方法的有效性。