A neural network for the analysis and monitoring of stress calls of pigs

P.C. Schön; B. Puppe; G. Manteuffel

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A neural network for the analysis and monitoring of stress calls of pigs

In: Precision livestock farming

Authors:

P.C. Schön

P.C. Schön schoen@fbn-dummerstorf.de

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B. Puppe

B. Puppe
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G. Manteuffel

G. Manteuffel
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Type:: Chapter

Pages:: 143–148

DOI:: https://doi.org/10.3920/9789086865154_022

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In recent years sound analysis has become an increasingly important tool to interpret the behaviour, the health condition, and the well-being of animals. This applies especially to stress situations. The paper presents a procedure that can classify stress calls of domestic pigs. Using linear prediction coding (LPC) an extremely compact short time representation of the call, with a relatively low effort of calculation and a low number of features (LPC-coefficients) was attained. Classification of the LPC-vectors employed artificial neural networks, trained with the LPC-coefficients of pigs’ stress calls, other non-stress calls, and noise. After training the network was able to classify stress vocalizations of pigs in practical farming environments.

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Precision livestock farming

E-Book ISBN:: 9789086865154

Publisher:: Wageningen Academic

Print Publication Date:: 10 Oct 2003

Subjects
- Life Sciences
  - General
  - Animal & Veterinary

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A neural network for the analysis and monitoring of stress calls of pigs

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Precision livestock farming

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