Artículo
Computational method for segmentation and classification of ingestive sounds in sheep
Milone, Diego Humberto
; Rufiner, Hugo Leonardo
; Galli, Julio Ricardo; Laca, E.A.; Cangiano, Carlos Alberto
Fecha de publicación:
03/2009
Editorial:
Elsevier
Revista:
Computers and Eletronics in Agriculture
ISSN:
0168-1699
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
In this work we propose a novel method to analyze and recognize automatically sound signals of chewing and biting. For the automatic segmentation and classification of acoustical ingestive behaviour of sheep the method use an appropriate acoustic representation and statistical modelling based on hidden Markov models. We analyzed 1813 seconds of chewing data from four sheep eating two different forages typically found in grazing production systems, orchardgrass and alfalfa, each at two sward heights. Because identification of species consumed when in mixed swards is a key issue in grazing science, we tested the possibility to discriminate species and sward height by using the proposed approach. Signals were correctly classified by forage and sward height in 67% of the cases, whereas forage was correctly identified 84% of the time. The results showed an overall performance of 82% for the recognition of chewing events.
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Articulos(CCT - SANTA FE)
Articulos de CTRO.CIENTIFICO TECNOL.CONICET - SANTA FE
Articulos de CTRO.CIENTIFICO TECNOL.CONICET - SANTA FE
Citación
Milone, Diego Humberto; Rufiner, Hugo Leonardo; Galli, Julio Ricardo; Laca, E.A.; Cangiano, Carlos Alberto; Computational method for segmentation and classification of ingestive sounds in sheep; Elsevier; Computers and Eletronics in Agriculture; 65; 2; 3-2009; 228-237
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