Detection of Strangers Based on Dog’s Sound
Anisha Rachel John1, Anita H.B2
1Anisha Rachel John, Department of Computer Science, Christ Deemed to Be University, Bangalore (Karnataka), India.
2Anita H.B, Department of Computer Science, Christ Deemed to Be University, Bangalore (Karnataka), India.
Manuscript received on 07 April 2019 | Revised Manuscript received on 20 April 2019 | Manuscript published on 30 April 2019 | PP: 111-114 | Volume-8 Issue-6, April 2019 | Retrieval Number: F3406048619/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Nowadays, people having a pet at home are increasing. Usually, dog is the favorite pet animal for most of the people in the world. Dogs are more capable of identifying strangers in the surroundings than humans. The proposed work identifies the strangers based on the barking sound of the dog. In this anticipated work, multiple features are extracted from the dog’s barking sound using Fast Fourier Transform and Statistical based methods. The classification is done using Naïve Bayes classifier. The dataset contains 770 barking audio files of 8 dogs. Whenever known and unknown person comes home, the sounds of the dogs are recorded. The classification result for identifying the stranger is 79.1094%.
Keyword: Autocorrelation, Fast Fourier Transform (FFT), NavieBayes, Sound Classification.
Scope of the Article: Network Based Applications