The idea of Machine Translation may be traced back to the 17th century, in the work of René Descartes. It first started being used for its actual purpose many years later, in the late 1970s, in institutions like the European Comission and then at big corporations such as Caterpillar and General Motors. With the advent of the Internet, the evolution of Machine Translation significantly sped up, resulting in advanced technologies like today’s Statistical Machine Translation.
In software localization, Machine Translation (or Automatic Translation) can be used in a number of processes.
Machine Translation as a pseudolocalization technique
Pseudolocalization means simulating the localization process before beginning the real translation work. It is done for testing purposes, without involving any human translators, to see what the localized software would look like in the target language. Pseudolocalization helps avoid issues related to text expansion, character encoding, string hard-coding and other aspects. Out of the available pseudolocalization techniques, Machine Translation is probably the best to imitate what would happen during the actual human translation process.
Machine Translation as part of the post-editing process
Although controversial among some translators, companies around the world are increasingly seeking the use of translation technologies like Google Translate or Bing Translator to localize apps or websites. They couple the input from these technologies with post-editing, with the aim of speeding up translation turnaround time and decreasing translation cost. There are different levels of post-editing, from light, which only ensures readability and factual correctness of the translated content, to full, which produces translated content that complies with established grammar and style rules and terminology.
POEditor’s Automatic Translation feature
At POEditor, we offer our users the possibility to automatically translate software strings using the Machine Translation APIs from either Google (Google Translate) or Microsoft (Bing Translator).
Both Google Translate and Bing Translator use Statistical Machine Translation, a translation algorithm based on language pattern matching. While Machine Translation can provide satisfactory results when translating words or single sentences, it is well known that translation accuracy can dramatically decrease as the complexity of the text to be translated increases.
We always recommend using human translation when you localize a website or an app, if you want to provide a high quality experience to the user. In case you’re on a budget and can’t hire professional translators, you can always use POEditor to crowdsource translation or maybe use a mix of Automatic Translation and translation crowdsourcing.