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Cow identification and recognition of condition with its vocalization

机译：母牛识别和识别条件及其发声

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摘要

The objective of this research is automatization of livestock management using the animal voice which may be considered as the expression of animal demands. In this paper, vocalizations of seven cows were analyzed under hungry and weaning conditions to recognize individual cow and condition important in livestock management. It was assumed that the voice was produced by the auto-regressive process and the frequency characteristics of voice were expressed with the linear prediction coefficients. These coefficients were utilized in the discriminant analysis using the Mahalanobis' generalized distance. The rate of exact recognition ranged from 23.4% to 77.8% for recognition of individual, and the average rate was 59.8%. The average rate of exact recognition was 92.4% for recognition of condition.
机译：本研究的目的是使用动物的声音自动化牲畜管理，这可能被认为是动物需求的表达。 在本文中，在饥饿和断奶条件下分析了七头奶牛的发声，以识别牲畜管理中的个体牛和条件。 假设通过自动回归过程产生的声音，并且用线性预测系数表示语音的频率特性。 使用Mahalanobis的广义距离在判别分析中使用这些系数。 确切识别的速度范围为个体的23.4％至77.8％，平均率为59.8％。 确切识别的平均速度为92.4％，以确认条件。

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