{"title":"一种自动检测重复口吃的计算机辅助算法","authors":"Junbo Zhang, Bin Dong, Yonghong Yan","doi":"10.1109/IALP.2013.32","DOIUrl":null,"url":null,"abstract":"An algorithm to detect Chinese repetitive stuttering by computer is studied. According to the features of repetitions in Chinese stuttered speech, improvement solutions are provided based on the previous research findings. First, a multi-span looping forced alignment decoding networks is designed to detect multi-syllable repetitions in Chinese stuttered speech. Second, branch penalty factor is added in the networks to adjust decoding trend using recursive search in order to reduce the error from the complexity of the decoding networks. Finally, we rejudge the detected stutters by calculating confidence to improve the reliability of the detection result. The experimental results show that compared to previous algorithm, the proposed algorithm can improve system performance significantly, about 18% average detection error rate relatively.","PeriodicalId":413833,"journal":{"name":"2013 International Conference on Asian Language Processing","volume":"81 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"A Computer-Assist Algorithm to Detect Repetitive Stuttering Automatically\",\"authors\":\"Junbo Zhang, Bin Dong, Yonghong Yan\",\"doi\":\"10.1109/IALP.2013.32\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An algorithm to detect Chinese repetitive stuttering by computer is studied. According to the features of repetitions in Chinese stuttered speech, improvement solutions are provided based on the previous research findings. First, a multi-span looping forced alignment decoding networks is designed to detect multi-syllable repetitions in Chinese stuttered speech. Second, branch penalty factor is added in the networks to adjust decoding trend using recursive search in order to reduce the error from the complexity of the decoding networks. Finally, we rejudge the detected stutters by calculating confidence to improve the reliability of the detection result. The experimental results show that compared to previous algorithm, the proposed algorithm can improve system performance significantly, about 18% average detection error rate relatively.\",\"PeriodicalId\":413833,\"journal\":{\"name\":\"2013 International Conference on Asian Language Processing\",\"volume\":\"81 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-08-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 International Conference on Asian Language Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IALP.2013.32\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Conference on Asian Language Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IALP.2013.32","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Computer-Assist Algorithm to Detect Repetitive Stuttering Automatically
An algorithm to detect Chinese repetitive stuttering by computer is studied. According to the features of repetitions in Chinese stuttered speech, improvement solutions are provided based on the previous research findings. First, a multi-span looping forced alignment decoding networks is designed to detect multi-syllable repetitions in Chinese stuttered speech. Second, branch penalty factor is added in the networks to adjust decoding trend using recursive search in order to reduce the error from the complexity of the decoding networks. Finally, we rejudge the detected stutters by calculating confidence to improve the reliability of the detection result. The experimental results show that compared to previous algorithm, the proposed algorithm can improve system performance significantly, about 18% average detection error rate relatively.