{"title":"Dynamic time warping for speech recognition with training part to reduce the computation","authors":"Sun Xihao, Y. Miyanaga","doi":"10.2299/JSP.18.89","DOIUrl":null,"url":null,"abstract":"Dynamic time warping (DTW) is a popular automatic speech recognition (ASR) method based on template matching[1] [2]. DTW algorithm compares the parameters of an unknown word with the parameters of one reference template. But the recognition rate is limited. To increase the number of reference templates for the same word will improve the recognition rate, but it will lead to spend a lot of computing time and memory resource. In this paper we proposed a method to reduce the number of reference templates, thus reduces the computing time and memory resource and also keep the high recognition rate.","PeriodicalId":260263,"journal":{"name":"International Symposium on Signals, Circuits and Systems ISSCS2013","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Symposium on Signals, Circuits and Systems ISSCS2013","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2299/JSP.18.89","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
Dynamic time warping (DTW) is a popular automatic speech recognition (ASR) method based on template matching[1] [2]. DTW algorithm compares the parameters of an unknown word with the parameters of one reference template. But the recognition rate is limited. To increase the number of reference templates for the same word will improve the recognition rate, but it will lead to spend a lot of computing time and memory resource. In this paper we proposed a method to reduce the number of reference templates, thus reduces the computing time and memory resource and also keep the high recognition rate.
动态时间规整(Dynamic time warping, DTW)是一种流行的基于模板匹配的自动语音识别(ASR)方法[1][2]。DTW算法将一个未知词的参数与一个参考模板的参数进行比较。但是识别率是有限的。增加对同一词的参考模板的数量可以提高识别率，但会消耗大量的计算时间和内存资源。本文提出了一种减少参考模板数量的方法，从而减少了计算时间和内存资源，同时保持了较高的识别率。
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