Various countries are associated with different languages. However, because the world is becoming a global village, most schools around the world are now teaching at least one foreign language. Despite the influx of foreign languages to many countries worldwide, a big number of adults does not have the abilities to speak any given foreign language. This has prompted a technological advancement to aid greater number of people who are unable to communicate in foreign languages with respect to their country of origin. Machine translation (MT) is a new technology that caters for translation from one language to another.
MT is a barely new technology and is characterized by limited popularity worldwide. Unlike computer-based technologies, which are widely used, MT entails incorporation of tools and environmental development, language design programming, verifications, and specifications of quality improvement, among others. With MT, vast amount of texts can be translated from one language into another. All aspects of languages and linguistics compatible with computations are covered by MT. Various companies have thought of the MT software that does the automatic translation from a particular language into other languages, thereby helping individuals and enterprises to be effective in speaking multiple languages more efficiently.
SYSTRAN is the leading solution provider for MT in the market. The group has its headquarters in France, although it has another branch based in North America. The software provided by SYSTRAN does translation instantly from a given text into fifty two different languages to enhance understanding and publication of information. This ensures that entities are able to use any data irrespective of the language that is used in its authorship. An extension of SYSTRAN`s position in 2009 to introduce the first engine for MT translation hybrid also assisted in improvement of language translation. With the company being the leading innovator, it is easier to combine the merits of technological developments in reference to linguistics, and those of the techniques in statistics, leading to an enhancement of the software`s ability to validate existing translations. The fact that SYSTRAN`s MT is quick and easy to use, allows users of the software to handle any specific undertaking or domain to gain and achieve quality translations with respect to cost effectiveness in publication.
Application of Machine Translation in Education
Learning has been made easier with technological innovations. However, one needs to have an understanding of at least one foreign language so as to pursue his/her education in a foreign country. Often, willing scholars experience difficulties in adapting to foreign systems of learning due to language barriers in their new destinations of learning. Nevertheless, with the discovery of MT, such scholars will undoubtedly pursue their education by using the MT software, ensuring that they are able to understand the new languages they encounter. For example, an American is able to translate lengthy texts written in French into various other languages, provided the software is in place. Consequently, scholars are in a position to read any text irrespective of the languages used as well.
MT is widely used in statistical research for learning purposes. Syntax Based Statistical Machine Translation translates English content into many foreign languages for the readers who do not know how to read English. The Phase Based Statistical Machine Translation helps in learning translations of sequences with arbitrary wording from parallel texts directly. Word Alignment is yet another application of MT to education. Here, the Statistical Machine Translation makes use of translated data from existing bodies. This system works when a corresponding word is identified or the word alignment in the translated data is a vital step when conducting training processes. In education, MT can be used in Language Modeling (LM), where language models are a critical component in Statistical Machine Translations. The LM helps to highlight readable and fluent work in translation processes.
In conclusion, MT will give a huge boost to the education sector if widely embraced, as more students can access materials written in various languages.