{"title":"A Novel Application System of Assessing the Pronunciation Differences Between Chinese Children and Adults.","authors":"Xiaoyang Zhang, Lei Xue, Zhi Zhang, Yiwen Zhang","doi":"10.2174/1874120701610010091","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Health problems about children have been attracting much attention of parents and even the whole society all the time, among which, child-language development is a hot research topic. The experts and scholars have studied and found that the guardians taking appropriate intervention in children at the early stage can promote children's language and cognitive ability development effectively, and carry out analysis of quantity. The intervention of Artificial Intelligence Technology has effect on the autistic spectrum disorders of children obviously.</p><p><strong>Objective and methods: </strong>This paper presents a speech signal analysis system for children, with preprocessing of the speaker speech signal, subsequent calculation of the number in the speech of guardians and children, and some other characteristic parameters or indicators (e.g cognizable syllable number, the continuity of the language).</p><p><strong>Results: </strong>With these quantitative analysis tool and parameters, we can evaluate and analyze the quality of children's language and cognitive ability objectively and quantitatively to provide the basis for decision-making criteria for parents. Thereby, they can adopt appropriate measures for children to promote the development of children's language and cognitive status.</p><p><strong>Conclusion: </strong>In this paper, according to the existing study of children's language development, we put forward several indicators in the process of automatic measurement for language development which influence the formation of children's language. From the experimental results we can see that after the pretreatment (including signal enhancement, speech activity detection), both divergence algorithm calculation results and the later words count are quite satisfactory compared with the actual situation.</p>","PeriodicalId":39121,"journal":{"name":"Open Biomedical Engineering Journal","volume":"10 ","pages":"91-100"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/16/47/TOBEJ-10-91.PMC4988092.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Open Biomedical Engineering Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2174/1874120701610010091","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2016/1/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Health problems about children have been attracting much attention of parents and even the whole society all the time, among which, child-language development is a hot research topic. The experts and scholars have studied and found that the guardians taking appropriate intervention in children at the early stage can promote children's language and cognitive ability development effectively, and carry out analysis of quantity. The intervention of Artificial Intelligence Technology has effect on the autistic spectrum disorders of children obviously.
Objective and methods: This paper presents a speech signal analysis system for children, with preprocessing of the speaker speech signal, subsequent calculation of the number in the speech of guardians and children, and some other characteristic parameters or indicators (e.g cognizable syllable number, the continuity of the language).
Results: With these quantitative analysis tool and parameters, we can evaluate and analyze the quality of children's language and cognitive ability objectively and quantitatively to provide the basis for decision-making criteria for parents. Thereby, they can adopt appropriate measures for children to promote the development of children's language and cognitive status.
Conclusion: In this paper, according to the existing study of children's language development, we put forward several indicators in the process of automatic measurement for language development which influence the formation of children's language. From the experimental results we can see that after the pretreatment (including signal enhancement, speech activity detection), both divergence algorithm calculation results and the later words count are quite satisfactory compared with the actual situation.