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Poster 16
Tatjana Schmidt presents Poster 16 during the poster sessions in the Aula.
Session theme 1: Development, validation and automated measurements of indicators of animal welfare
AUTOMATED VOCAL TYPE CLASSIFICATION AS A TOOL TO
IDENTIFY STRESS IN PIGLETS DURING AN OPEN-FIELD TEST AND
DIFFERENT CASTRATION PROCEDURES
T. Schmidt 1 , B. Bünger 2 , T. Horn 1 , E. von Borell 1
1 Institute of Agricultural- and Nutritional Sciences, Martin-Luther-University Halle-Wittenberg, Germany
2 Institute of Animal Welfare and Animal Husbandry, Federal Research Centre for Animal Health, Friedrich-
Loeffler-Institute, Celle, Germany
Previous investigations proved that the automatic detection of high frequency stress-calls in pigs
serves as reliable tool in welfare research. Our approach focuses on the automatic classification of
the different classes of piglets' vocalisations - grunting, squealing and screaming. We hypothesise
that this differentiation serves essential functions in pig communication and thus might reveal
information about their well-being.
In a first experiment, 3, 285 vocalisations from 42 piglets (German PIC; 7, 13, 19d) and in a second
experiment 11, 089 vocalisations from 22 piglets (German Landrace; 24 to 27d) were analysed for
23 different vocal characteristics. A discriminant function for the three vocal types was derived
from recordings made under laboratory-like conditions during castration procedures. A second
discriminant function based on 12 vocal characteristics was derived from non-calibrated
measurements of the relative energy content. The comparison of the two classifications showed an
86.7% agreement. Differences in the vocal type distributions between the piglets castrated with and
without anaesthesia remained significant (χ2-test, p