{"title":"基于音频预处理方法的卷积神经网络环境声音分类性能比较","authors":"W. Oh","doi":"10.7776/ASK.2020.39.3.143","DOIUrl":null,"url":null,"abstract":": This paper presents the effect of the feature extraction methods used in the audio preprocessing on the classification performance of the Convolutional Neural Networks (CNN). We extract mel spectrogram, log mel spectrogram, Mel Frequency Cepstral Coefficient (MFCC)","PeriodicalId":42689,"journal":{"name":"Journal of the Acoustical Society of Korea","volume":null,"pages":null},"PeriodicalIF":0.2000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Comparison of environmental sound classification performance of convolutional neural networks according to audio preprocessing methods\",\"authors\":\"W. Oh\",\"doi\":\"10.7776/ASK.2020.39.3.143\",\"DOIUrl\":null,\"url\":null,\"abstract\":\": This paper presents the effect of the feature extraction methods used in the audio preprocessing on the classification performance of the Convolutional Neural Networks (CNN). We extract mel spectrogram, log mel spectrogram, Mel Frequency Cepstral Coefficient (MFCC)\",\"PeriodicalId\":42689,\"journal\":{\"name\":\"Journal of the Acoustical Society of Korea\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.2000,\"publicationDate\":\"2020-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of the Acoustical Society of Korea\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.7776/ASK.2020.39.3.143\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ACOUSTICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the Acoustical Society of Korea","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.7776/ASK.2020.39.3.143","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ACOUSTICS","Score":null,"Total":0}
Comparison of environmental sound classification performance of convolutional neural networks according to audio preprocessing methods
: This paper presents the effect of the feature extraction methods used in the audio preprocessing on the classification performance of the Convolutional Neural Networks (CNN). We extract mel spectrogram, log mel spectrogram, Mel Frequency Cepstral Coefficient (MFCC)
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