Precision livestock farming dictates the use of advanced technologies to understand, analyze, assess and finally optimize a farm’s production collectively as well as the contribution of each single animal. This work is part of a research project wishing to steer the dairy farms’ producers to more ethical rearing systems. To study cow’s welfare, we focus on reciprocal vocalizations including mother-offspring contact calls. We show the set-up of a suitable audio capturing system composed of automated recording units and propose an algorithm to automatically detect cow vocalizations in an indoor farm setting. More specifically, the algorithm has a two-level structure: a) first, the Hilbert follower is applied to segment the raw audio signals, and b) second the detected blocks of acoustic activity are refined via a classification scheme based on hidden Markov models. After thorough evaluation, we demonstrate excellent detection results in terms of false positives, false negatives and confusion matrix.

Automatic detection of cow/calf vocalizations in free-stall barn / S. Ntalampiras, A. Pezzuolo, S. Mattiello, M. Battini, M. Brscic - In: 2020 43rd International Conference on Telecommunications and Signal Processing (TSP)[s.l] : IEEE, 2020. - ISBN 9781728163765. - pp. 41-45 (( Intervento presentato al 43. convegno International Conference on Telecommunications and Signal Processing (TSP) tenutosi a Milano nel 2020 [10.1109/TSP49548.2020.9163522].

Automatic detection of cow/calf vocalizations in free-stall barn

S. Ntalampiras
;
S. Mattiello;M. Battini;
2020

Abstract

Precision livestock farming dictates the use of advanced technologies to understand, analyze, assess and finally optimize a farm’s production collectively as well as the contribution of each single animal. This work is part of a research project wishing to steer the dairy farms’ producers to more ethical rearing systems. To study cow’s welfare, we focus on reciprocal vocalizations including mother-offspring contact calls. We show the set-up of a suitable audio capturing system composed of automated recording units and propose an algorithm to automatically detect cow vocalizations in an indoor farm setting. More specifically, the algorithm has a two-level structure: a) first, the Hilbert follower is applied to segment the raw audio signals, and b) second the detected blocks of acoustic activity are refined via a classification scheme based on hidden Markov models. After thorough evaluation, we demonstrate excellent detection results in terms of false positives, false negatives and confusion matrix.
Precision livestock farming; cow/calf vocalization; acoustic signal processing, vocalization detection; audio pattern recognition
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2434/758172
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