The smaller the population size of a given spoken language, it can be expected the less likely the interface language of a particular software product will be available in that language. Also, the smaller the market for such a product, the less incentive there is for the software developer to make the effort to translate the interface to a particular language. This results in the limited availability of niche products in minority languages (Simultrans,2013).
Translating text into a different languages for users of assistive technology (AT) or as part of the development process when designing ATs requires forethought, as there are additional elements that need to be considered as mentioned in Language and Language impact on layout. As with all language translations there cannot be a straight forward word for word translation and several checks need to be made to ensure overall accuracy. A simple tip at the outset is to try automatically translating a document back into its native language or to ask a second translator to check the output and even to ‘crowdsource’ the translation and pick the best version on offer.
Context is vital and the provision of a list of words in a resource file representing menu items or content from a web page is not sufficient for anyone working on a translation as can be demonstrated with the use of machine translation or automatic translation tool such as Google Translate with some words related to computer use. The initial Google translation of words from English to Spanish were ‘run‘ as a person running ‘correr’ but on the computer it is ‘abrir’, to ‘save‘ money is ‘ahorre’ and to ‘save’ a file is ‘quardar’; ‘home‘ when you live there is ‘hogar’ or ‘casa’ but the first page on a website or in a program is ‘inicio’ and ‘view‘ in terms of seeing is ‘visión’ but on the computer screen it is ‘vista’. Google provided up to five options for some words and in some cases the options were related to the position of a word in a sentence and in others it was down to meaning. So using the words in a full sentence can help as can be seen below but this is not always an option provided by developers and errors can still creep in such as ‘casa‘ in the example below: “View the options before you close the windows and exit the program. Then run the file. save the changes and return home.” “Ver las opciones antes de cerrar las ventanas y salga del programa. A continuación, ejecute el archivo. guardar los cambios y regresar a casa” Even though there have been enormous strides made in accuracy rates and it can reduce costs, research has shown that data extraction from machine translation remains unreliable in many languages.(Balk et al. 2012) For those with print impairments the slightest errors in text can reduce comprehension and cause confusion with abandonment of the technology or at the very least a wish to refrain from reading the information presented, especially if it is being read aloud by a screen reader that does not allow an overview of the whole text to aid context.
One important thing to understand is that these new-generation translation tools — Google Translate and Google Conversation alike ������������������������� do not do what human translators do. They do not deconstruct the text, analyze its grammatical structure (which human translators do, even if subconsciously), figure out the meaning and then reconstruct it in another language. In effect, Google Translate/Conversation do not translate. They match. More specifically, they match (bits of) the original text with best translations, where “best” means most frequently found in a large corpus such as the World Wide Web. (Pereltsvaig, 2011)
Crowdsourcing, as described in a Wired article (Howe, 2006), allows many people to offer their services to carry out a task that might be too much for one to undertake and can be achieved by many at a lower cost. It might be a the collection of images for use by others or captioning of video’s for those with hearing impairments. In this case