标题：Insect Sound Recognition Based on Convolutional Neural Network
作者：Dong, Xue; Yan, Ning; Wei, Ying
作者机构：[Dong, Xue; Yan, Ning; Wei, Ying] Shandong Univ, Sch Informat Sci & Engn, Jinan, Shandong, Peoples R China.
会议名称：3rd IEEE International Conference on Image, Vision and Computing (ICIVC)
会议日期：JUN 27-29, 2018
来源：2018 IEEE 3RD INTERNATIONAL CONFERENCE ON IMAGE, VISION AND COMPUTING (ICIVC)
关键词：characteristic extraction; contrast-limit adaptive histogram; equalization; enhanced spectrogram; deep learning
摘要：A novel insect sound recognition system using enhanced spectrogram and convolutional neural network is proposed. Contrast-limit adaptive histogram equalization (CLAHE) is adopted to enhance R-space spectrogram. Traditionally, artificial feature extraction is an essential step of classification, introducing extra noise caused by subjectivity of individual researchers. In this paper, we construct a convolutional neural network (CNN) as classifier, extracting deep feature by machine learning. Mel-Frequency Cepstral Coefficient (MFCC) and chromatic spectrogram have been compared with enhanced R-space spectrogram as feature image. Eventually, 97.8723% accuracy rate is achieved among 47 types of insect sound from USDA library.