I’m a native Hebrew Speaker. Hebrew, as well as Arabic and several other languages, is a Right-to-Left (abbreviated ‘RTL’) language, meaning that it is written from Right to Left. Translators and other content creators working with bidirectionality (abbreviated ‘BiDi’) content – i.e. text containing both Left-to-Right (abbreviated ‘LTR’) and Right-to-Left characters and segments – are facing some unique challenges when it comes to formatting the text correctly. The development of the Unicode Bidirectional Algorithm and the growing support that it has enjoyed in the last decade or so have significantly improved how softwares handle BiDi content. Today all modern Operating Systems – for the desktop and mobile – support BiDi virtually out-of-the-box. Usually there is still a setting or two to tweak, but long gone are the days of installing awkward languages packs and/or workarounds to overcome or mask some of the technical limitations of BiDi support.
Despite these advancements, some issues still remain. The algorithm is not perfect and although it makes life much easier, the difference in directionality is still a concern and something to keep in mind when working with BiDi content. The algorithm should be perceived as a mechanism that lays down the technical foundations upon which the BiDi content is built. It is largely the responsibility of the content creators to understand how the BiDi algorithm works and use best practices when preparing the content.
In this article I will attempt to explain how the BiDi algorithm parses and handles the directionality of text, its shortcomings, and describe some of the most common BiDi issues and how to solve them.
This article focuses on BiDi issues in a word processor and Translation Environment Tool (abbreviated ‘TEnTs’) enviroments, but the principles and solutions described here apply globally. For details about the corresponding terminology in a plain text or (X)HTML enviroment, please see Directionality of Paragraphs and documents section below.
If you are interested in the tl;dr version of this article, please jump to the Takeaway section.
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