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Speech/Music Discrimination via Energy Density Analysis

机译:通过能量密度分析言语/音乐歧视

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In this paper we suggest to apply a new feature, called Minimum Energy Density (MED), in discrimination of audio signals between speech and music. Our method is based on the analysis of local energy for 1 or 2.5 seconds audio signals. An elementary analysis of the probability for the power distribution is an effective tool supporting the decision making system. We compare our feature with Percentage of Low Energy Frames (LEF), Modified Low Energy Ratio (MLER) and examine their efficiency for two separate speech/music corpora.
机译:在本文中,我们建议在语音和音乐之间的音频信号辨别中应用一个名为最小能量密度(MED)的新功能。我们的方法基于对局部能量的分析1或2.5秒的音频信号。对配电概率的基本分析是支持决策系统的有效工具。我们将功能与低能量框架(LEF),改进的低能量比(MIRL)进行了比较,并检查了两个单独的演讲/音乐语料库的效率。

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