Machine Translation In NLP

6 min readDec 29, 2021

How will we feel if suppose we are communicating with someone and they don’t understand what we are talking or our language? Right, we don’t feel good at all. The topic in this blog is all about knowing or understanding the language. As the title suggests that the topic is related to the translation and natural language processing. Basically the machine translation translate the one natural language to other.

The main thing about is that it does it’s work in very short amount of time. This blog covers different subtopics related to machine translation as specified in the following points :

What is machine translation and how it works.
What are the different types of machine translation in NLP.
What are the advantages of machine translation.
What are the applications of the machine translation.
What are the differences between machine and human translation.
Conclusion

What is Machine translation in NLP and how does it work?

Machine translation is nothing but the automated translation. It uses computer tools for the translating one natural language into other language without any assistance from the humans.

Machine translation provides the replacements for the atomic words in the single characteristic language for the words in the other language. The higher complicated translations can be performed using corpus method considering the better treatment of the contrast in the phonetic typology, translation of the idioms and express acknowledgement. Human like translation is not still possible for some of the systems but may be it’s even possible in the future.

Different types of machine translation :

There mainly four types of machine translation.

SMT (Statistical machine translation) :

This methods basically based on the statistical model which mainly depends on the resources of very large volumes of the bilingual content. In this method the correspondence is created between the words of the source language and the objective language. We can take the example of google translate for the same.

For the basic translation the SMT is an very good approach but with the help of this translation we can’t achieve great efficiency like we can say that the translation may be wrong sometimes. Following are some of the SMT models :

Syntax-based translation
Phrase-based translation
Hierarchical phrase-based translation
Word-based translation

2. RBMT (Rule-based machine translation) :

The basics of the grammatical rules can be translated with the help of the RBMT. In this method the translate sentence is created with the help of the grammatical examination of the source language and the objective language. The main disadvantage of this method is that it takes more time because of the substantial reliance on the dictionaries and broad editing.

3. HMT (Hybrid machine translation) :

HMT stands for hybrid machine translation and it is basically the combination of the SMT and RBMT. This method gives a good quality translation with the help of the translation memory. This type also have some of the disadvantages like it requires large amount of editing and also some times it require human translators. Following are the some of approaches to HMT :

Multi-pass
Statistical rule generation
Multi-engine
Confidence-based

4. NMT (Neural machine translation) :

This method makes use of the neural network models (based on human brain) and as the end result produces the statistical model with the help of which the translation can be made successfully. The main advantage of this type is that it gives a solitary system that can be prepared to unravel the source and target text. This type of machine translation does not depend upon the specific system unlike the system in case of the SMT.

Advantages of machine translation :

One of the main advantage of the machine translation is the speed as we get our text translated within short period of time which is quite useful thing in many situations. Yes the human translator can do the translation more accurately but they can not catch the speed of the machine.

Based on the requirements that you have if you train the machine properly it gives the better results and the cost effective solution to your problem as it will be less expensive than the human translator. Other advantage of the machine translation is that it can reuse the important words wherever they are required for better translation.

Applications of the machine translation :

Machine translation can be used in the large number of the applications we can take the example of the business travel, travel industries and many more some of the applications are as follows :

Text translation :

text-level and the sentence-level translation applications can require the automated translation most of the times. Inquiry and recovery inputs and the translation of the text extracted from the images are some applications come under the sentence-level translation. The transition of the archives with organized data and the translation of the unadulterated reports are the some of the applications that come under the text-level translation.

Speech translation :

Today the voice search or the voice input became more popular application in field of the human-computer interaction because of the fast advancement of the mobile applications and the discourse translation became the important application. The basic cycle of discourse interpretation is “source language discourse source language text-target language text-target language discourse”.

Also there are many other applications as well.

Difference between machine translation and human translation :

When it come to the cost of the translation then the machine translation will definitely preferred because that is more cost effective than the human translation. Also if we consider about the speed of the translation the speed of the machine is better than the human translation so then also the machine translation will be getting first place. If there is large amount of the text or data to be translated then definitely the machine will do the work in the very less amount of the time.

On other hand the human translation includes the actual brainpower so the translation will be more accurate and reliable as compared to the machine translation as machine translation uses the artificial intelligence or the machine learning for modifying the text from one language to the ther language.

Conclusion :

We can consider the machine translation as the tool which helps the translator to achieve a motive. It is basically modification of the old system of the translation. The machine translators analyze the given content and separate that into the short expressions so that they can be easily translated and then reconstruct the original content.

image courtesy :

References :

K. Jiang and X. Lu, “Natural Language Processing and Its Applications in Machine Translation: A Diachronic Review,” 2020 IEEE 3rd International Conference of Safe Production and Informatization (IICSPI), 2020, pp. 210–214, doi: 10.1109/IICSPI51290.2020.9332458.
B. N. V. N. Raju and M. S. V. S. B. Raju, “Statistical Machine Translation System for Indian Languages,” 2016 IEEE 6th International Conference on Advanced Computing (IACC), 2016, pp. 174–177, doi: 10.1109/IACC.2016.41.
S. Satpathy, S. P. Mishra and A. K. Nayak, “Analysis of Learning Approaches for Machine Translation Systems,” 2019 International Conference on Applied Machine Learning (ICAML), 2019, pp. 160–164, doi: 10.1109/ICAML48257.2019.00038.
https://www.analyticssteps.com/blogs/4-types-machine-translation-nlp
https://www.qblocks.cloud/blog/natural-language-processing-machine-translation