{"title":"测试语音识别器的能力,以衡量数字语音传输编码算法的有效性","authors":"C. Chernick, S. Leigh, K. L. Mills, R. Toense","doi":"10.1109/MILCOM.1999.821447","DOIUrl":null,"url":null,"abstract":"Modern communication channels, such as digital cellular telephony, often convey human speech in a highly encoded form. Methods that rely on human subjects to evaluate the quality of such channels are too costly to deploy on a large scale; thus, automated methods are often used to model quality as perceived by humans. Traditional automated methods that use signal to noise ratios (SNR) to judge the quality of channels do not model human perception well when applied to highly encoded speech. For this reason, researchers investigate alternative means to objectively measure the quality of such channels. We explore the feasibility and applicability of using automated speech recognition technology to model human perception of the quality of communication channels that carry highly encoded (compressed) human speech.","PeriodicalId":334957,"journal":{"name":"MILCOM 1999. IEEE Military Communications. Conference Proceedings (Cat. No.99CH36341)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1999-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":"{\"title\":\"Testing the ability of speech recognizers to measure the effectiveness of encoding algorithms for digital speech transmission\",\"authors\":\"C. Chernick, S. Leigh, K. L. Mills, R. Toense\",\"doi\":\"10.1109/MILCOM.1999.821447\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Modern communication channels, such as digital cellular telephony, often convey human speech in a highly encoded form. Methods that rely on human subjects to evaluate the quality of such channels are too costly to deploy on a large scale; thus, automated methods are often used to model quality as perceived by humans. Traditional automated methods that use signal to noise ratios (SNR) to judge the quality of channels do not model human perception well when applied to highly encoded speech. For this reason, researchers investigate alternative means to objectively measure the quality of such channels. We explore the feasibility and applicability of using automated speech recognition technology to model human perception of the quality of communication channels that carry highly encoded (compressed) human speech.\",\"PeriodicalId\":334957,\"journal\":{\"name\":\"MILCOM 1999. IEEE Military Communications. Conference Proceedings (Cat. No.99CH36341)\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1999-10-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"18\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"MILCOM 1999. IEEE Military Communications. Conference Proceedings (Cat. No.99CH36341)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MILCOM.1999.821447\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"MILCOM 1999. IEEE Military Communications. Conference Proceedings (Cat. No.99CH36341)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MILCOM.1999.821447","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Testing the ability of speech recognizers to measure the effectiveness of encoding algorithms for digital speech transmission
Modern communication channels, such as digital cellular telephony, often convey human speech in a highly encoded form. Methods that rely on human subjects to evaluate the quality of such channels are too costly to deploy on a large scale; thus, automated methods are often used to model quality as perceived by humans. Traditional automated methods that use signal to noise ratios (SNR) to judge the quality of channels do not model human perception well when applied to highly encoded speech. For this reason, researchers investigate alternative means to objectively measure the quality of such channels. We explore the feasibility and applicability of using automated speech recognition technology to model human perception of the quality of communication channels that carry highly encoded (compressed) human speech.