{"title":"VOIS: The First Speech Therapy App Specifically Designed for Myanmar Hearing-Impaired Children","authors":"A. Thida, Nway Nway Han, Sheinn Thawtar Oo, Sheng Li, Chenchen Ding","doi":"10.1109/O-COCOSDA50338.2020.9295024","DOIUrl":null,"url":null,"abstract":"The hearing-impaired children's education is challenging because they are unlikely to develop normal speech and language ability. We propose a mobile application VOIS, which is the first speech therapy application for hearing-impaired children in Myanmar. This mobile application uses a Convolutional Neural Network (CNN) based offline Burmese speech recognition system. It can help hearing-impaired children to train with the language pre-requisites at their own pace. To effectively help the hearing-impaired children to understand the basics of the language, this system provides one-syllable and two-syllable structured Myanmar words collected in real-life educational and communication materials. The experimental result shows that the prediction rate of this system is nearly 60%. Experiments also show the hearing-impaired children can learn and operate the language freely through a simple practice using this application. The expectation is that this application can bring both opportunities and life-quality improvements for children with hearing loss in Myanmar.","PeriodicalId":385266,"journal":{"name":"2020 23rd Conference of the Oriental COCOSDA International Committee for the Co-ordination and Standardisation of Speech Databases and Assessment Techniques (O-COCOSDA)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 23rd Conference of the Oriental COCOSDA International Committee for the Co-ordination and Standardisation of Speech Databases and Assessment Techniques (O-COCOSDA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/O-COCOSDA50338.2020.9295024","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
The hearing-impaired children's education is challenging because they are unlikely to develop normal speech and language ability. We propose a mobile application VOIS, which is the first speech therapy application for hearing-impaired children in Myanmar. This mobile application uses a Convolutional Neural Network (CNN) based offline Burmese speech recognition system. It can help hearing-impaired children to train with the language pre-requisites at their own pace. To effectively help the hearing-impaired children to understand the basics of the language, this system provides one-syllable and two-syllable structured Myanmar words collected in real-life educational and communication materials. The experimental result shows that the prediction rate of this system is nearly 60%. Experiments also show the hearing-impaired children can learn and operate the language freely through a simple practice using this application. The expectation is that this application can bring both opportunities and life-quality improvements for children with hearing loss in Myanmar.