Jan 28, 2020 0 Categories :Engineering Core

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We are blessed to find ourselves living in a world that encapsulates a wide range of cultures each, with their means of communication. The world as we know it is getting more and more globalized by day and, the requirement of information technology is reaching the doorsteps of those who are incapable of communicating in the language of the internet. More and more businesses are turning to machine translation to work with people from all cultures across the globe. To really get the importance of translations, here is a key figure: in 2015 Google Translate processed 100 billion words a day.

What exactly is Machine Translation? By definition, Machine translations are a form of computational linguistics and language engineering which uses software to translate text or speech from one language to another. Let us take a look at some of the translation engines that exist. 

Hybrid MT Engines:

The two most common engines are rule-based and statistical engines. These engines differ in the way that they process and analyze content that is often combined within the same system and known as hybrid MT rule-based machine translation.

Rule-Based (RB) MT Engines:

Another type of engines is the RB MT engines which use linguistic rules to break down the content it produces more predictable output for terminology and grammar through the use of customized terminology lists to fine-tune the engine the ability to correct every error with a targeted rule. Such rule-based engines don’t need a large and structured set of texts also known as a bilingual corpus to create the translation system.

Statistical MT Engines (SMT):

Statistical models are used to generate the translation of the source content. These engines don’t analyze text based on language rules. Instead, the statistical model is built by analyzing bilingual corpus and requires an appropriate volume of bilingual content to do so. This is the main idea behind what we call Natural Language Processing in artificial intelligence today.

Machine translation has found a great deal of implementation in the field of assistance content, customer support, user documentation, and, in many other fields. 

Robotics happens to be a very important field for the implementation of machine translations. A mid product of machine translation can be considered as the stage where the language is first converted to the form where a machine can understand it, i.e Numbers and Vectors. Speech recognition as we call it today will also play a big role in making the new age Jarvis (The actual one, not the android app available on play store) and Friday (Iron Man fans would know) too. This short article is written to give a very basic outlook on language processing to help the readers discover their interest and follow into it.

I found this interesting video on the subject of Natural language Processing. You may go through this and decide your interest.

No Thoughts on Introduction to Machine Translation

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