{"title":"测量文本输入任务中的错误:Levenshtein字符串距离统计的应用","authors":"R. W. Soukoreff, I. Scott MacKenzie","doi":"10.1145/634067.634256","DOIUrl":null,"url":null,"abstract":"We propose a new technique based on the Levenshtein minimum string distance statistic for measuring error rates in text entry research. The technique obviates the need to artificially constrain subjects to maintain synchronization with the presented text, thus affording a more natural interaction style in the evaluation. Methodological implications are discussed, including the additional need to use keystrokes per characters (KSPC) as a dependent measure to capture the overhead in correcting errors.","PeriodicalId":351792,"journal":{"name":"CHI '01 Extended Abstracts on Human Factors in Computing Systems","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"220","resultStr":"{\"title\":\"Measuring errors in text entry tasks: an application of the Levenshtein string distance statistic\",\"authors\":\"R. W. Soukoreff, I. Scott MacKenzie\",\"doi\":\"10.1145/634067.634256\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose a new technique based on the Levenshtein minimum string distance statistic for measuring error rates in text entry research. The technique obviates the need to artificially constrain subjects to maintain synchronization with the presented text, thus affording a more natural interaction style in the evaluation. Methodological implications are discussed, including the additional need to use keystrokes per characters (KSPC) as a dependent measure to capture the overhead in correcting errors.\",\"PeriodicalId\":351792,\"journal\":{\"name\":\"CHI '01 Extended Abstracts on Human Factors in Computing Systems\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-03-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"220\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"CHI '01 Extended Abstracts on Human Factors in Computing Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/634067.634256\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"CHI '01 Extended Abstracts on Human Factors in Computing Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/634067.634256","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Measuring errors in text entry tasks: an application of the Levenshtein string distance statistic
We propose a new technique based on the Levenshtein minimum string distance statistic for measuring error rates in text entry research. The technique obviates the need to artificially constrain subjects to maintain synchronization with the presented text, thus affording a more natural interaction style in the evaluation. Methodological implications are discussed, including the additional need to use keystrokes per characters (KSPC) as a dependent measure to capture the overhead in correcting errors.