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首页> 外文会议>IEEE International Conference on Acoustics, Speech and Signal Processing;ICASSP >Recording environment identification using acoustic reverberation
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Recording environment identification using acoustic reverberation

机译：使用声学混响记录环境识别

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摘要

Acoustic environment leaves its fingerprints in the audio recording captured in it. Acoustic reverberation and background noise are generally used to characterize an acoustic environment. Acoustic reverberation depends on the shape and the composition of a room, therefore, differences in the estimated reverberation can be used in a forensic and ballistic settings and acoustic environment identification (AEI). We describe a framework that uses acoustic reverberation to characterize recording environment and use it for AEI. Inverse filtering is used to estimate the reverberation component from audio recording. A 48-dimensional feature vector consisting of Mel-frequency Cepstral Coefficients and Logarithmic Mel-spectral Coefficients is used to capture traces of reverberation. A multi-class support vector machine (SVM) classifier is used for AEI. Experimental results show that the proposed system can successfully identify a recording environment for regular as well as blind AEI.
机译：声学环境会将其指纹留在其中捕获的音频记录中。声学混响和背景噪声通常用于表征声学环境。声学混响取决于房间的形状和组成，因此，估计的混响的差异可用于法医和弹道设置以及声学环境识别（AEI）。我们描述了一个使用声学混响来表征录音环境并将其用于AEI的框架。逆滤波用于从录音中估计混响分量。由梅尔频率倒谱系数和对数梅尔谱系数组成的48维特征向量用于捕获混响的轨迹。多类支持向量机（SVM）分类器用于AEI。实验结果表明，所提出的系统可以成功地识别常规和盲目AEI的记录环境。

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