Diagnosis of patients ducks based on their voices and using artificial intelligence methods

Document Type : Research Paper

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Abstract

In this paper, a smart method is designed in order to classify healthy and illness ducks using their emission voice. For this purpose, firstly, the birds based on their healthy condition are divided into the different categories and then their voices are saved using a microphone and data acquisition card. Gained signals were transformed from time-domain signal to frequency domain using Fast Fourier Transform (FFT). Then, 5 statistical features are extracted from both time and frequency signals namely, mean, standard division, root mean square, variance and kurtosis. Two classifiers which are artificial neuralnetworks (ANN) and support vector machine (SVM) are used, in order to acquire the bird classification in healthy and sick accuracy. The accuracy of ANN classifier in detection of healthy birds within sick and weak birds was determined 75% and 82.1 % based on the time and frequency domain of the sound signals, respectively. The accuracy of SVM classifier in detection of healthy birds within sick and weak birds was determined 85.7 % and 92.8 % based on the time and frequency domain of the sound signals, respectively.

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References

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Iranian Journal of Biosystems Engineering
Volume 47, Issue 2 - Serial Number 2
September 2016
Pages 307-318

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History

  • Receive Date: 08 January 2014
  • Revise Date: 21 November 2014
  • Accept Date: 05 January 2016

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