Posts Tagged 'machine translation'

Google Translate

On the following lines, it will be analyzed one of the most succesful translators of this century-Google Translate. This translator is a free on-line statistical machine service owned by Google Inc that translates immediately a lot of different languages (57) such as Polish, German, Dutch, Spanish… However, it has to be said that some languages are better translated than others, in other words, some languages are supported by Google translate and others languages are called by the company “alpha languages”, this is to say that these languages have lower quality in their translations.

It is possible to translate long texts, but the system limits the number of paragraphs. Nevertheless, if the user wants to translate completely a website, Google Translate gives him or her the opportunity to use Google chrome which is a fast free browser that translates websites automatically in many languages. Not only  does Google translate give you the opportunity to use Google chrome, but also other tools such as to the Google translated search (the information that you are searching probably will not be in your own language; the system searches the best contribution and translates it to your own language) or the iphone version which allows voice input.

The aim of this enterprise is “to make information universally accessible, regardless of the language in which it is written” That is why it has been improving  since it started. Nowadays, it can be done many things that could not be done at the beginning. For example, in the first version, only English could be translated to some other languages, now it can be done the other way round. Moreover, it is also possible to have the romanization written for languages such as Chinese or Greek and, in the last version launched in January 2011, it is also possible to see different possible translations for a specific word. A good way that helps this translator to improve is that the user himself can increase the quality of  translations by suggesting improvements or uploading his translations memories into Google Translate’s Translator Toolkit. Furthermore, the service itself asks the user sometimes alternate translations for technical terms.

But, how does this translator work? As it has been said, Google Translate is a Statistical Machine Translator (SMT) which is a way of translating texts completely different from the traditional rule-based translations. The rule-based  machine translations were used some years ago and they applied the rules and grammars of the language that was being translated. However, Linguists knew that not all languages had the same rules (e.g the order of some languages is subject- verb-object but in others is verb- subject-object) that is why the translations were not very good.

 Then, it began statistical machine translations where the computer looks for patterns in millions of documents. This documents had already been translated by human beings and thanks to them the computer can know more or less how the translation should be. However, the translations are not always perfect and the quality of them depends mainly on the number of documents that the computer can analyze to see patterns. That is why Google Translate can translate better, for example, German than Basque, it has more German documents than Basque Documents. Franz Josef Och is the main head in Google and he is in favour of Statistical machine translators. The documents that are available for the machine are taken from United Nations documents.

Finally, this way to translate texts has advantages. For instance, the quality is better than in rule-based translations, also, the translations are more natural and we have better use of resources. But, there are some disadvantages and problems with: sentence alignment, different word orders, compound words, idioms, morphology

Do not hesitate to see the following video that explains how SMT works . If you are interested in knowing more about the problems Google Translate has, you can see the portfolio I did commenting the main problems here:



Machine Translation.(Questionnaire 2 and questionnaire 3)

There are other research topics apart from Speaker Recognition and Computational Semantics. One that I think is really interesting is Machine Translation. This term has its origin in the 17th century when René Descartes (French philosopher, mathematician…) proposed a universal language. He wanted that the same ideas in different languages had the same symbol.

In these times, Machine Translation or MT is a field of computational linguistics that investigate how to translate text or speech from one natural language to another using computer software. It has to be said that the invention is extremely useful in areas where formal language is used such as legal or administrative documents. Nevertheless, when it is a colloquial or familiar text, the machine normally makes lots of mistakes because it translates the text word by word. We can see an example in the following picture.


Many computer scientists, linguists… have tried to improve this machine with more or less success. We could mention Hans Uszkoreit who I have talked about in a previous article. He worked in a machine translation project while he was staying at Austin. Moreover, there have being carried out several projects all over the world. For example, one in the National Centre for Language Technology in Ireland or the Norwegian-English Machine Translation in Norway.


List of research topics mentioned in major sites on Human Language Technologies. (Questionnaire 2)

After having surfed among a wide range of sites on Human Language Technologies, these are the research topics that I have selectionated:

1. Language Checking.

2. Computational Semantics.

3. Machine Translation.

4. Computer Aided Language Learning.

5. Semántica, pragmática y discurso.

6. Resolución de la ambigüedad léxica.

7. Multimodality.

8. Natural Language Parsing.

9. Speech Retrieval.

10. Spoken Dialogue Systems.

11. Speaker Recognition.


  • Projects (2009, June, 9) In Language Technology World. Retrieved: 9:30, June 19, 2009, from
  • NCLT Research Groups (2009, April, 15) In National Centre for Language Technology. Retrieved: 9:50, June 19, 2009, from
  • Objetivos. In Sociedad Española para el Procesamiento del Lenguage Natural. Retrieved 10:07, June 19, 2009, from
  • Main Conference Program (2006-2007) In ACL 2007. Retrieved 10:20, June 19, 2009 from



Hans Uszkoreit (Q1)

Hans Uszkoreit was born in Rostock (Germany) in 1950. He studied Linguistics and Computer Science at the Technical University of Berlin. While he was studying there, he worked as an editor and writer for the magazine Zitty. It has to be said that this magazine was co-founded by him. Then, he was given a Fulbright Grant and continued his studies at the University of Texas at Austin. The Fulbright Grant was created by J. William Fulbright (senator of Arkansas in the period of the Second World War) and the reason for creating this educational help was to make inhabitants from Europe and the United States understand one another better. It was also a good way to encourage tolerance and understanding between countries.

Returning to Hans Uszkoreit’s stay at Austin, not only did he study but he also worked in a machine translation project at the Linguistics Research Center. Finally, in 1984 he received the Ph.D. in linguistics from the University of Texas. Since then, he has been doing several things. Indeed, he is member of a wide range of associations (European Academy of Sciences, European Network of Language and Speech …)


Nowadays, the scholar is a Professor of Computational Linguistics at Saarland University. Apart from serving as Scientific Director at the German Research Center for Artificial Intelligence (DFKI) where he heads the DFKI Language Technology Lab. Moreover, he has written a lot of publications and he has also written poems in English and in German. In conclusion, Hans Uszkoreit is an excellent professor and researcher, so people should take him into account when talking about linguistics and computer science.


June 2018
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