Mel-frequency Cepstral Coefficient-Vector Quantization Implementation for Voice Detection of Rice-Eating Birds in The Rice Fields
Rahmat, Romi Fadillah
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The losses suffered by the farmers due to bird attack could reach of 15 – 50 percent of harvest yield. The peasants use conventional pesticides and this still conducted manually which is very inefficient. Therefore, this study has the purpose of developing an application of rice-eating bird voice detector. This application can automatically detect the sounds of birds that are eating the rice to facilitate the farmers to monitor and repel the birds' presence in the paddy to reduce losses during harvest seasons. Mel Frequency Cepstral Coefficients-Vector Quantization (MFCC-VQ) was used as the method for bird’s voice recognition. The feature of voice signals captured via microphone will be extracted using the Mel Frequency Cepstral Coefficients (MFCC) algorithm. The extracted audio signal is then identified whether the sound is a bird or not using the Vector Quantization (VQ) algorithm. The identification result will generate the output of a firing sound as an action to cast out and scare the birds away from the fields. The result of this study is that the sound of birds was detected depending on the arrival of birds in the field such as during the morning, afternoon and evening. The result also showed that the further the distance of the microphone from the sound source, the smaller the intensity of the voice and the noisy the state of the environment on the detection process, the smaller the accuracy percentage.