{"title":"Environment Recognition from Audio Using MPEG-7 Features","authors":"G. Muhammad, K. Alghathbar","doi":"10.1109/EM-COM.2009.5402978","DOIUrl":null,"url":null,"abstract":"In this paper, we introduce a full use of MPEG-7 Audio features for environment recognition from audio for different multimedia applications. Environment recognition from audio files is a growing area of interest, however, compared to other branches of multimedia it is a less researched one. To recognize environment, we utilize total of 17 temporal and spectral MPEG-7 Audio low- level descriptors as features. The performance is compared with Mel-frequency cepstral coefficients (MFCC) features. Experimental results show a significant improvement of the proposed MPEG-7 based environment recognition over that of the conventional MFCC based features. Zero-crossing rate is appended with the MPEG-7 based feature to yield even better performance. The best performance is achieved with combined MFCC, MPEG-7 and zero- crossing features. Index Items: Environment recognition, MPEG-7 Audio, MFCC, multimedia.","PeriodicalId":290107,"journal":{"name":"2009 Fourth International Conference on Embedded and Multimedia Computing","volume":"302 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Fourth International Conference on Embedded and Multimedia Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EM-COM.2009.5402978","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 18
Abstract
In this paper, we introduce a full use of MPEG-7 Audio features for environment recognition from audio for different multimedia applications. Environment recognition from audio files is a growing area of interest, however, compared to other branches of multimedia it is a less researched one. To recognize environment, we utilize total of 17 temporal and spectral MPEG-7 Audio low- level descriptors as features. The performance is compared with Mel-frequency cepstral coefficients (MFCC) features. Experimental results show a significant improvement of the proposed MPEG-7 based environment recognition over that of the conventional MFCC based features. Zero-crossing rate is appended with the MPEG-7 based feature to yield even better performance. The best performance is achieved with combined MFCC, MPEG-7 and zero- crossing features. Index Items: Environment recognition, MPEG-7 Audio, MFCC, multimedia.