With the readily available tools online for translation, many think this quick, free, and easy option is good enough for business use as well. However, there are two sides of the coin to look at when deciding on whether or not to use machine translation for your business. Reliability, consistency, and extensive translations are just a few of the topics that are discussed in business use translation.
So, how can you use machine translation tools for your business, and when should you turn to professional interpreters?
Evolution of Machine Translation
| Year | Event |
| 1924 | Estonia – The world’s first known proposal for machine trasnslation which involved a typewriter translator. |
| 1933 | Georges Artsrouni works on device since 1929 and patents his general-purpose device with multiple applications. |
| 1933 | Patent (author’s certificate) awarded to Peter Petrovich Toyanskii for his proposal which uses a mechanized dictionary for translation between languages. |
| 1939-1944 | Russia – Troyanskii takes his proposal to the Academy of Sciences in hopes to work with linguists. Not much comes out of these conversations which continued until 1944. |
| 1949 | United States – Warren Weaver of the Rockefeller Foundation presents proposal for machine translation which is based on information theory, successes with breaking code during WWII and speculation about underlying, universal principles of natural language. |
| 1954 | New York City – An experiment at Georgetown IBM gave the first public demonstration of machine translation. The system contained 250 words and translated 49 sentences (carefully selected) from Russian to English, mostly in the Chemistry field. |
| 1958-1960 | Yehoshua BarHillel was a linguist who traveled around the world visiting the various machine translation centers in order to better understand how they work, and what work they were doing. A year later, BarHillel wrote a document to point out difficulties in the machine translators. The main argument was that the current methods of the time had no ways of resolving semantic ambiguities whose resolution required having an understanding of the terms being used. Such as the ambiguity arising from a single word having multiple meanings. |
| 1966 | ALPAC publishes a U.S. government commissioned report which concluded that machine translation is more expensive, slower and less accurate than human translation. The report went on to say that despite expenses, machine translation was not likely to match results of human translation in the near future. Recommendations were made in the report to develop tools to help translators. Tools like automatic dictionaries, and that some research in computational linguistics should continue to be supported. This report caused a significant decline for funding machine translation by the US government. And, to a smaller extent, in Russia and the UK. |
| 1968 | Peter Toma starts SYSTRAN. |
| 1970 | Bernard Scott starts Logos. |
| 1977 | The METEO System, developed at the Université de Montréal, is installed in Canada to translate weather forecasts from English to French and is translating close to 80,000 words per day or 30 million words per year until it is replaced by a competitor’s system on 30 September 2001. |
| 1984 | Makoto Nagao proposes example-based machine translation. The idea is to break down sentences into phrases (sub-sentential units). Then, learn the translations of those phrases using a corpus of examples. With enough phrases known, new sentences that combine existing phrases in a novel manner can be translated. |
| 1997 | The world’s first web translation tool, Babel Fish, is launched as a subdomain of the AltaVistasearch engine. The tool is created by Systran in collaboration with Digital Equipment Corporation. |
| 2006 | Google launches “Google Translate” |
Information received from wikipedia.org
The pros
- Most software is free.
- Quick results.
- Easy to use.
The cons
Unfortunately, machine translation produces results that are limited and not always reliable. There are said to be between 6 and 7 thousand languages that exist. What’s more, there is no such automated translation technology that is an expert at even the one thousand languages which hold most important today. To put this into even more perspective, the powerful and arguably most popular machine translation “Google Translate” only has the ability to handle a little over 100 languages today.
When can a small business use machine translation?
If you need to translate a quick email or website, then automated machine translation will probably work fine for you.
However, if you are looking to build relationships and have consistent contact with those who speak different languages, then having a professional translator is the more appropriate option.
If you need legal documents translated, or have a big conference you will need translation for, professional translation services are the most appropriate choice.
In short, a quick Google Translate search comes in handy for something small and easy, but there is still no match for the services of professional interpreters, especially for your business. You wouldn’t want to misinterpret a conversation or event that could leave you, and your business, in a bad position with a potential client. If you have more questions on this topic or would like to know more about professional translation services, please contact us at your convenience.