Takahisa Kishino, Sun Zhe, Roberto Marchisio, R. Micheletto
{"title":"Cross-modal codification of images with auditory stimuli: a language for the visually impaired","authors":"Takahisa Kishino, Sun Zhe, Roberto Marchisio, R. Micheletto","doi":"10.1167/17.10.1356","DOIUrl":null,"url":null,"abstract":"In this study we describe a methodology to realize visual images cognition in the broader sense, by a cross-modal stimulation through the auditory channel. An original algorithm of conversion from bi-dimensional images to sounds has been established and tested on several subjects. Our results show that subjects where able to discriminate with a precision of 95\\% different sounds corresponding to different test geometric shapes. Moreover, after brief learning sessions on simple images, subjects where able to recognize among a group of 16 complex and never-trained images a single target by hearing its acoustical counterpart. Rate of recognition was found to depend on image characteristics, in 90% of the cases, subjects did better than choosing at random. This study contribute to the understanding of cross-modal perception and help for the realization of systems that use acoustical signals to help visually impaired persons to recognize objects and improve navigation","PeriodicalId":298664,"journal":{"name":"arXiv: Neurons and Cognition","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv: Neurons and Cognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1167/17.10.1356","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In this study we describe a methodology to realize visual images cognition in the broader sense, by a cross-modal stimulation through the auditory channel. An original algorithm of conversion from bi-dimensional images to sounds has been established and tested on several subjects. Our results show that subjects where able to discriminate with a precision of 95\% different sounds corresponding to different test geometric shapes. Moreover, after brief learning sessions on simple images, subjects where able to recognize among a group of 16 complex and never-trained images a single target by hearing its acoustical counterpart. Rate of recognition was found to depend on image characteristics, in 90% of the cases, subjects did better than choosing at random. This study contribute to the understanding of cross-modal perception and help for the realization of systems that use acoustical signals to help visually impaired persons to recognize objects and improve navigation