Machine Translation

1. Introduction: In the words of the European Association for Machine Translation (EAMT): Machine translation (MT) is the application of computers to the task of translating texts from one natural language to another. The output of the machine translation, if not perfect, is of sufficient quality to be useful in a number of specific domains.

One of the oldest machine translation companies is SYSTRAN, founded by Dr. Peter Toma in 1968. Current machine translation software often allows for customisation by domain or profession - improving output by limiting the scope of allowable substitutions. Improved output quality can also be achieved by human intervention: for example, some systems are able to translate more accurately if the user has unambiguously identified which words in the text are names. With the assistance of these techniques, MT has proven useful as a tool to assist human translators, and in some cases can even produce output that can be used as is. However, current systems are unable to produce output of the same quality as a human translator, particularly where the text to be translated uses casual language.

2. Google Translate: Google Translate (https://translate.google.com) is a free, multilingual statistical machine-translation service provided by Google Inc. to translate written text from one language into another. Google Translate instantly translates text and web pages from one language to another language. Presently Google Translate supports 90 major languages of the world. Google Translate offers a web interface, mobile interfaces for Android and iOS, and an API that developers can use to build browser extensions, applications, and other software. For some languages, Google Translate can pronounce translated text, highlight corresponding words and phrases in the source and target text, and act as a simple dictionary for single-word input. If “Detect language” is selected, text in an unknown language can be identified.

In the web interface, users can suggest alternate translations, such as for technical terms, or correct mistakes. These suggestions are included in future updates to the translation process. If a user enters a URL in the source text, Google Translate will produce a hyperlink to a machine translation of the website. For some languages, text can be entered via an on-screen keyboard, handwriting recognition, or speech recognition.

Google Translate, like other automatic translation tools, has its limitations. The service limits the number of paragraphs and the range of technical terms that can be translated, and while it can help the reader to understand the general content of a foreign language text, it does not always deliver accurate translations.

3. Bing Translator: Bing Translator (http://www.bing.com/translator/) is a translation portal provided by Microsoft as part of its Bing services to translate texts or entire web pages into different languages. All translation pairs are powered by the Microsoft Translator, a statistical machine translation platform and web service, developed by Microsoft Research, as its backend translation software. As of November 2015, Bing Translator offers translations in 52 different language systems.

4. Babelfish (https://www.babelfish.com): Babelfish is a free online translator for users to translate phrases and sentences from one natural language to the other. It is a SaaS-based multilingual translation portal.

5. Apertium (http://www.apertium.org): Apertium (http://www.apertium.org) is a rule-based free and open source machine translation platform released under GNU General Public License.

6. Conclusion: Machine translation (MT) is a sub-field of computational linguistics that investigates the use of computer software to translate text or speech from one natural language to another. At its basic level, MT performs simple substitution of atomic words in one natural language for words in another. Using corpus techniques, more complex translations may be attempted, allowing for better handling of differences in linguistic typology, phrase recognition, and translation of idioms, as well as the isolation of anomalies. Although there is no system that provides the holy-grail of “Fully automatic high quality machine translation” (FAHQMT), many systems provide reasonable quality output.X

How to Cite this Article?

APA Citation, 7^th Ed.:  Barman, B. (2020). A comprehensive book on Library and Information Science. New Publications.

Chicago 16^th Ed.:  Barman, Badan. A Comprehensive Book on Library and Information Science. Guwahati: New Publications, 2020.

MLA Citation 8^th Ed:  Barman, Badan. A Comprehensive Book on Library and Information Science. New Publications, 2020.

Badan Barman at present working as an Assistant Professor in the Department of Library and Information Science, Gauhati University, Guwahati-781014, Assam, India. He is the creator of the LIS Links (http://www.lislinks.com) - India’s most popular social networking website for Library and Information Science professionals. He also created the UGC NET Guide (http://www.netugc.com) and LIS Study (http://www.lisstudy.com) website.