Sound Classification of Four Insect Classes

2024/12/16 by Yinxuan Wang, Sudip Vhaduri, Wang, Yinxuan +1 · 1 citation
Psychology · Biochemistry, Genetics and Molecular Biology · Agricultural and Biological Sciences · #Animal and Plant Science Education #Lepidoptera: Biology and Taxonomy #Orthoptera Research and Taxonomy

paper · pdf · doi:10.48550/arxiv.2412.12395

Abstract

The goal of this project is to classify four different insect sounds: cicada, beetle, termite, and cricket. One application of this project is for pest control to monitor and protect our ecosystem. Our project leverages data augmentation, including pitch shifting and speed changing, to improve model generalization. This project will test the performance of Decision Tree, Random Forest, SVM RBF, XGBoost, and k-NN models, combined with MFCC feature. A potential novelty of this project is that various data augmentation techniques are used and created 6 data along with the original sound. The dataset consists of the sound recordings of these four insects. This project aims to achieve a high classification accuracy and to reduce the over-fitting problem.

Cited by

• Early Detection of Furniture-Infesting Wood-Boring Beetles Using CNN-LSTM Networks and MFCC-Based Acoustic Features

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