Identifying Indian Cattle Behaviour Using Acoustic Biomarkers

Ruturaj Patil, Hemavathy B, Sanat Sarangi, Dineshkumar Singh, Rupayan Chakraborty, Sanket Junagade, Srinivasu Pappula

Abstract: A system to recognise sounds from some major cattle breeds commonly found in India and linking them to intents reflecting specific behaviour along with associated needs is proposed. Cattle breeds in India consist of a mix of indigenous and exotic breeds where Sindhi, Sahiwal, and Gir make up a significant fraction of the indigenous breeds. Exotic breeds are Jersey and Holstein Friesian. Vocalisation from the animals in this cattle group is used to create a sound dataset comprising 120 utterances for over six intents where the intents were labelled by domain experts familiar with the animals and their behaviour. MFCCs and OpenSMILE global features from the audio signal with 6552 properties are used to model for intent recognition. The dataset is scaled and augmented with four different methods to 870 cattle sounds for the six classes. Two model architectures are created and tested on data for each method independently and with all of them together. The models are also tested on unseen