Automatic accessibility transcoding for flash content
Author(s) -
Daisuke Sato,
Hisashi Miyashita,
Hironobu Takagi,
Chieko Asakawa
Publication year - 2007
Publication title -
citeseer x (the pennsylvania state university)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.1145/1296843.1296852
Subject(s) - computer science , content (measure theory) , flash (photography) , world wide web , multimedia , the internet , transcoding , hypertext , web content , attractiveness , web accessibility , internet privacy , human–computer interaction , psychology , computer network , art , mathematical analysis , mathematics , psychoanalysis , visual arts , web standards
It is not surprising that rich Internet content, such as Flash and DHTML, is some of the most pervasive content because of its visual attractiveness to the sighted majority. Such visually rich content has been causing severe accessibility problems, especially for people with visual disabilities. For Flash content, the kinds of accessibility information necessary for screen readers is not usually provided in the existing content. A typical example of such missing data is the lack of alternative text for buttons, hypertext links, widget roles, and so on. One of the major reasons is that the current accessibility framework of Flash content imposes a burden on content authors to make their content accessible. As a result, adding support for accessibility tends to be neglected, and screen reader users are left out of the richer Internet experiences. Therefore, we decided to develop an automatic accessibility transcoding system for Flash content to allow users to access a wider range of existing content, and to reduce the workload for content authors by using an automatic repair algorithm. It works as a client-side transcoding system based on the internal object model inside the Flash content. It adds and repairs accessibility information for existing Flash content, so screen readers can present more accessible information to users. Our experiment using the pilot system showed that 55% of the missing alternative texts for buttons in the tested websites could be added automatically.
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