Many of us at some point in our lives have turned to Google to translate words, sentences, or maybe even our homework, from one language to another, and have received results - to varying degrees of accuracy - in the blink of an eye.
Google Translate accomplishes this feat using a process called “statistical machine translation,” which involves methods that are central to computer science.
The process starts with an input - the phrase or word that you would like translated. In the normal computing process, the central processing unit would receive this input, and then request and write to and from its memory (cache, RAM, Hard drive, etc.). Google Translate works similarly; however, the memory that it draws from is not a universal list of words and phrases in every language; instead, its memory consists of an extensive record of millions of documents on the internet that have already been translated, including books, documents from the UN, and websites.
The algorithm that the software works with to produce its results involves a statistical computation. Every translated document is scanned and analyzed for statistically significant patterns, and once each pattern is identified, it is stored to be accessed as a reference pattern for future translations involving the specific language in which the document is written. Google Translate also uses the same algorithm when processing our input, comparing the pattern produced by your initial phrase to the patterns stored in the software's database. The more closely an input pattern matches a reference pattern, the stronger its correlation. To produce the final output, Google Translate simply chooses the translation with the highest correlation. Interestingly, every time a translation is made on Google, it is added to its database to be used as a reference pattern in the future, influencing the probability that the specific output translation will be made again.
Because Google Translate interprets both inputs and outputs as patterns, there is a great tendency of your translation to become altered when adding or removing seemingly insignificant words. Each word changes the pattern that the software receives and interprets, which ultimately determines the content of your output. Not only does the content and syntax of your input impact the accuracy of your output, but also the languages that you are translating between. For relatively obscure languages, there are fewer documents available to serve as reference, and therefore fewer patterns for the software to analyze. Because of this, there is a high degree of variance in the accuracy of translation depending on the language, with such languages as English producing translations of high quality, and languages such as Igbo producing those of low quality.
Still don't understand?
Check out the video below for a highly animated but highly informative explanation, by the one and only, Google.
Image Source:
http://jess3.com/google-translate-video/
Video Source:
https://www.youtube.com/watch?v=_GdSC1Z1Kzs
Text Source:
Still don't understand?
Check out the video below for a highly animated but highly informative explanation, by the one and only, Google.
Image Source:
http://jess3.com/google-translate-video/
Video Source:
https://www.youtube.com/watch?v=_GdSC1Z1Kzs
Text Source:
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