使用mel频率倒谱系数的音频检测

Uppu Jithendra, Usha Mittal, Priyanka Chawla
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引用次数: 0

摘要

缺乏与任何建议的方法进行比较的基准结果是声事件检测研究中最基本的挑战之一。不同的研究探索不同的事件和数据集,使得很难区分新的和现有的方法。本研究使用ESC 50数据集计算平均精度和平均AUC。我们明确地采用基于高斯混合模型的组件描述,并用线性和非线性支持向量机将其固化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Audio Detection using Mel-frequency Cepstral Coefficients
The lack of benchmark findings for comparison with any suggested approach is one of the most fundamental challenges in sound event detection research. Distinct research explore different sets of events and datasets, making it difficult to distinguish between new and existing methods. We calculated the average accuracy and mean AUC using the ESC 50 dataset in this research. We employ a Gaussian Mixture model-based component depiction explicitly and solidify it with linear and non-linear Support Vector Machines.
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