{"title":"使用零频率滤波提取声门关闭和打开的瞬间","authors":"K. Deepak, K. Ramesh, S. Prasanna","doi":"10.1109/INDICON.2014.7030502","DOIUrl":null,"url":null,"abstract":"In this paper a simple method is proposed using zero frequency filtering (ZFF) of a close approximate glottal flow derivative (GFD) to extract glottal closure (GCI's) and opening instants (GOI's) from speech. The GFD is obtained from iterative adaptive inverse filtering (IAIF) which contains such instants. It is observed that GCI's can be located by positive zero crossings of zero frequency filtered signal (ZFFS) obtained from GFD. However, GOI's can be located using GFD from negative to positive zero crossing regions of ZFFS. The method is evaluated using CMU-Arctic databases and compared with other state of the art methods under clean and noisy conditions. The performance of the proposed methods are robust under noisy conditions and comparable to other existing methods.","PeriodicalId":409794,"journal":{"name":"2014 Annual IEEE India Conference (INDICON)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Extraction of glottal closure and opening instants using zero frequency filtering\",\"authors\":\"K. Deepak, K. Ramesh, S. Prasanna\",\"doi\":\"10.1109/INDICON.2014.7030502\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper a simple method is proposed using zero frequency filtering (ZFF) of a close approximate glottal flow derivative (GFD) to extract glottal closure (GCI's) and opening instants (GOI's) from speech. The GFD is obtained from iterative adaptive inverse filtering (IAIF) which contains such instants. It is observed that GCI's can be located by positive zero crossings of zero frequency filtered signal (ZFFS) obtained from GFD. However, GOI's can be located using GFD from negative to positive zero crossing regions of ZFFS. The method is evaluated using CMU-Arctic databases and compared with other state of the art methods under clean and noisy conditions. The performance of the proposed methods are robust under noisy conditions and comparable to other existing methods.\",\"PeriodicalId\":409794,\"journal\":{\"name\":\"2014 Annual IEEE India Conference (INDICON)\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 Annual IEEE India Conference (INDICON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INDICON.2014.7030502\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 Annual IEEE India Conference (INDICON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INDICON.2014.7030502","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Extraction of glottal closure and opening instants using zero frequency filtering
In this paper a simple method is proposed using zero frequency filtering (ZFF) of a close approximate glottal flow derivative (GFD) to extract glottal closure (GCI's) and opening instants (GOI's) from speech. The GFD is obtained from iterative adaptive inverse filtering (IAIF) which contains such instants. It is observed that GCI's can be located by positive zero crossings of zero frequency filtered signal (ZFFS) obtained from GFD. However, GOI's can be located using GFD from negative to positive zero crossing regions of ZFFS. The method is evaluated using CMU-Arctic databases and compared with other state of the art methods under clean and noisy conditions. The performance of the proposed methods are robust under noisy conditions and comparable to other existing methods.