基于功率谱密度的蛋鸡声音检测方法
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“十二五”国家科技支撑计划资助项目(2014BAD08B05)和国家现代农业(蛋鸡)产业技术体系建设专项资金资助项目(CARS—41)


Detection of Laying Hens Vocalization Based on Power Spectral Density
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    摘要:

    利用声音连续监测动物生长过程的缺点是无效声音数据量大。为了获得便于研究人员使用的小数据量并同时反映动物行为信息的声音,引入分类识别方法对原始声音进行处理。以栖架饲养环境中的含有海兰褐蛋鸡鸣叫声的声音片段和风机噪声片段为研究对象,基于不同类型声音在1000~1500Hz频率范围内的功率谱密度存在差异,对2种声音片段进行了分类识别。试验结果表明,该方法的全面正确识别率为95%,其中蛋鸡声音片段正确识别率为93.3%。该方法将有助于实现风机噪声环境中动物声音实时检测与提取,从而减少无用声音数据的储存与传输。

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    The purpose of this paper is to develop a method for automatically detecting vocalizations of laying hens from a large amount of original data. First, the original sound data were cut into 1 sec of length clips by using sound analysis software. Then, 130 clips including calls of Hy-Line Brown laying hens and 132 fan noise fragments were selected. Finally, an algorithm was developed for automatically identifying vocalization of laying hens and fan noise based on the discrepancies of 2 kinds of sounds’ power spectral density in 1000~1500Hz. The results showed that a 95% overall correct classification ratio was achieved and 93.3% of the vocalizations of laying hens were correctly identified. This approach can improve the efficiency during sound analysis and reduce the storage and transmission of useless sound.

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曹晏飞,陈红茜,滕光辉,赵淑梅,李乔伟.基于功率谱密度的蛋鸡声音检测方法[J].农业机械学报,2015,46(2):276-280,300. Cao Yanfei, Chen Hongqian, Teng Guanghui, Zhao Shumei, Li Qiaowei. Detection of Laying Hens Vocalization Based on Power Spectral Density[J]. Transactions of the Chinese Society for Agricultural Machinery,2015,46(2):276-280,300.

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  • 收稿日期:2014-01-27
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  • 在线发布日期: 2015-02-10
  • 出版日期: 2015-02-10
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