Dwisainstia Aponno, A. Arifin, M. Fatoni, M. Nuh, Takashi Watanabe
{"title":"多传感器手套在印尼语手语辅助翻译中的应用评价","authors":"Dwisainstia Aponno, A. Arifin, M. Fatoni, M. Nuh, Takashi Watanabe","doi":"10.1109/CENIM56801.2022.10037541","DOIUrl":null,"url":null,"abstract":"Individuals who suffer in speaking and hearing are known as people with hearing and speech impairment. Sign language is used by them to communicate. Nevertheless, the general public does not fully comprehend sign language. In this study, assistive technology for the Indonesian Sign Language Interpretation System was developed to convert the alphabet sign into text. The system incorporates the usage of flex sensors, pressure sensor, and MPU6050 module. After the development, the evaluation for this interpreter is carried out. The classifier was able to identify 24 out of 26 alphabets with detection error frequently occurring in the letters N and R with an accuracy of 94% in the second experiment. By using a specific classification and including more test data, this study expected outcome can be heightened. The results show that the classification method, along with the tool, may be used effectively as a speech and hearing aid.","PeriodicalId":118934,"journal":{"name":"2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Evaluation of Multi-Sensor Gloves Development as an Assistive Interpreter for Indonesian Sign Language\",\"authors\":\"Dwisainstia Aponno, A. Arifin, M. Fatoni, M. Nuh, Takashi Watanabe\",\"doi\":\"10.1109/CENIM56801.2022.10037541\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Individuals who suffer in speaking and hearing are known as people with hearing and speech impairment. Sign language is used by them to communicate. Nevertheless, the general public does not fully comprehend sign language. In this study, assistive technology for the Indonesian Sign Language Interpretation System was developed to convert the alphabet sign into text. The system incorporates the usage of flex sensors, pressure sensor, and MPU6050 module. After the development, the evaluation for this interpreter is carried out. The classifier was able to identify 24 out of 26 alphabets with detection error frequently occurring in the letters N and R with an accuracy of 94% in the second experiment. By using a specific classification and including more test data, this study expected outcome can be heightened. The results show that the classification method, along with the tool, may be used effectively as a speech and hearing aid.\",\"PeriodicalId\":118934,\"journal\":{\"name\":\"2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM)\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-11-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CENIM56801.2022.10037541\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CENIM56801.2022.10037541","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Evaluation of Multi-Sensor Gloves Development as an Assistive Interpreter for Indonesian Sign Language
Individuals who suffer in speaking and hearing are known as people with hearing and speech impairment. Sign language is used by them to communicate. Nevertheless, the general public does not fully comprehend sign language. In this study, assistive technology for the Indonesian Sign Language Interpretation System was developed to convert the alphabet sign into text. The system incorporates the usage of flex sensors, pressure sensor, and MPU6050 module. After the development, the evaluation for this interpreter is carried out. The classifier was able to identify 24 out of 26 alphabets with detection error frequently occurring in the letters N and R with an accuracy of 94% in the second experiment. By using a specific classification and including more test data, this study expected outcome can be heightened. The results show that the classification method, along with the tool, may be used effectively as a speech and hearing aid.