S. Musale, Kalyani Gargate, Vaishnavi Gulavani, Samruddhi Kadam, S. Kothawade
{"title":"Indian sign language recognition and search results","authors":"S. Musale, Kalyani Gargate, Vaishnavi Gulavani, Samruddhi Kadam, S. Kothawade","doi":"10.32629/jai.v6i3.1000","DOIUrl":null,"url":null,"abstract":"Sign language is a medium of communication for people with hearing and speaking impairment. It uses gestures to convey messages. The proposed system focuses on using sign language in search engines and helping specially-abled people get the information they are looking for. Here, we are using Marathi sign language. Translation systems for Indian sign languages are not much simple and popular as American sign language. Marathi language consists of words with individual letters formed of two letter = Swara + Vyanjan (Mulakshar). Every Vyanjan or Swara individually has a unique sign which can be represented as image or video with still frames. Any letter formed of both Swara and Vyanjan is represented with hand gesture signing the Vyanjan as above and with movement of signed gesture in shape of Swara in Devnagari script. Such letters are represented with videos containing motion and frames in particular sequence. Further the predicted term can be searched on google using the sign search. The proposed system includes three important steps: 1) hand detection; 2) sign recognition using neural networks; 3) fetching search results. Overall, the system has great potential to help individuals with hearing and speaking impairment to access information on the internet through the use of sign language. It is a promising application of machine learning and deep learning techniques.","PeriodicalId":70721,"journal":{"name":"自主智能(英文)","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"自主智能(英文)","FirstCategoryId":"1093","ListUrlMain":"https://doi.org/10.32629/jai.v6i3.1000","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Sign language is a medium of communication for people with hearing and speaking impairment. It uses gestures to convey messages. The proposed system focuses on using sign language in search engines and helping specially-abled people get the information they are looking for. Here, we are using Marathi sign language. Translation systems for Indian sign languages are not much simple and popular as American sign language. Marathi language consists of words with individual letters formed of two letter = Swara + Vyanjan (Mulakshar). Every Vyanjan or Swara individually has a unique sign which can be represented as image or video with still frames. Any letter formed of both Swara and Vyanjan is represented with hand gesture signing the Vyanjan as above and with movement of signed gesture in shape of Swara in Devnagari script. Such letters are represented with videos containing motion and frames in particular sequence. Further the predicted term can be searched on google using the sign search. The proposed system includes three important steps: 1) hand detection; 2) sign recognition using neural networks; 3) fetching search results. Overall, the system has great potential to help individuals with hearing and speaking impairment to access information on the internet through the use of sign language. It is a promising application of machine learning and deep learning techniques.