用于广播电台分析的语音/音乐辨别

2017 International Conference on Systems, Signals and Image Processing (IWSSIP) Pub Date : 2017-05-01 DOI:10.1109/IWSSIP.2017.7965606

Stanisław Kacprzak, Blazej Chwiecko, B. Ziółko

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引用次数: 7

摘要

最小能量密度(MED)是一种计算效率高的特征，用于区分广播电台节目中的语音和音乐音频信号。所提出的二值分类器是基于测试两个特征:通道内的能量分布和能量差。我们分析了来自10个波兰广播电台的240小时的信号。我们的分析使我们能够提供有关特定广播电台内容的信息。

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Speech/music discrimination for analysis of radio stations

A computationally efficient feature, called Minimum Energy Density (MED) was applied to discriminate audio signals between speech and music in the radio stations programs. The presented binary classifier is based on testing two features: energy distribution and differences between energy in channels. We analyzed 240 hours of signals, from 10 Polish radio stations. Our analysis enables us to provide information about content of particular radio stations.

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来源期刊

2017 International Conference on Systems, Signals and Image Processing (IWSSIP)

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