When not to use machine translation?

"Machine translation is a powerful tool that can be used to translate text from one language to another quickly and easily. However, it is important to remember that machine translation is not perfect and can sometimes produce inaccurate or misleading translations. Here are some situations where you should not use machine translation: - When the translation is critical. Machine translation is not reliable enough for use in situations where the translation is critical, such as medical or legal documents. In these cases, it is always best to use a human translator. - When the text is creative or idiomatic. Machine translation struggles to translate creative or idiomatic text, such as poetry, song lyrics, or proverbs. In these cases, the translation will often be inaccurate or nonsensical. - When the text is culturally sensitive. Machine translation can sometimes produce translations that are insensitive to the target culture. For example, a machine translation of a joke might not be funny in the target language, or a machine translation of a political speech might offend the target audience. - When the text is long or complex. Machine translation is more accurate for short, simple texts. For long or complex texts, it is often better to use a human translator."

What is machine translation and when to use it?

Q: Which is typically used for machine translation?

"In recent years, there has been a growing trend towards using neural machine translation for machine translation. Neural machine translation is a type of statistical machine translation that uses artificial neural networks to learn how to translate text. Neural machine translation has been shown to be more accurate than traditional statistical machine translation, and it is also more consistent. However, neural machine translation is still under development, and it can be less accurate for translating certain types of text, such as technical or legal documents. So, which type of machine translation is typically used? The answer depends on the specific needs of the translation project. For projects that require high accuracy, rule-based machine translation may be the best option. For projects that require speed and consistency, statistical machine translation may be a better choice. And for projects that require the latest technology, neural machine translation may be the best option."

Imagine a business dinner that gathers African, Asian, American, and European tongues, everyone in his own dialect!

Exactly, How would they communicate? That’s why Translation exists.

It is said that the history of human communication and Translation is inseparable.

We’ll put an example, Emily in Paris (a Netflix show), she is an American girl who travels to work in France while speaking zero French and faces many lingual challenges.

Imagine now that she has no tools to assist her in initiating conversations with French people. Keep this example as we will use it later on in this article.

Simply put, Machine Translation tools are applications designed with Artificial intelligence (AI) programs that enable us to change a large number of texts within a variety of language pairs supported. For Example:

Google Translate
Amazon Translate
CrossLang
DeepL
Microsoft Translator
Unbabel
Watson Language Translator

How do these tools work?

Machine translation is designed to convert an original text into another text while saving a large number of terminologies and definitions in its translation memory. so, what is Translation Memory?

Machine translation has 4 different types:

Rule-Based Machine Translation (RBMT)

RBMT tools mainly focus on grammatical rules to produce a translation, by analyzing the grammatical rules of both texts; source and target.

Statistical Machine Translation (SMT)

SMT tools create translations based on the analysis of bilingual texts, mainly relying on the statical models created. context is not considered with such types of tools.

Hybrid Machine Translation (HMT)

Hybrid MT tools are as the name implies; it is a combination of both SMT and RBMT tools.

Neural Machine Translation (NMT)

NMT is considered the most modern MT tool. It employs AI to learn languages and improve that knowledge.

Also, its engines seek to understand the context and provide an accurate prediction, as it’s designed based on the neural network of the human brain.

Translation cycle before and after MT tools

To ensure an accurate translation, you can’t think of a word-for-word process, you will need to pay careful attention to the meaning behind the text.

For this to happen, the translation process used to go through a set of steps that we will mention in the following lines:

Also, each step requires a different linguist which makes the human translation process a bit slow and expensive.

On the other side, the process of implementing Machine Translation would be as follows:

Choose the text:

Not all content is suitable for MT tools. As a matter of fact: texts that require less creativity would fit.

Translation Ready content:

Make sure there is no misspelling or errors in the text, and prepare your translation Glossary.

Update your MT systems periodically:

MT systems can be trained and adapted using your preferred data and the input that will lead to more accurate results.

A post editor is a must:

MT alone won’t usually yield the best results. For a more accurate product, a Post Editor is needed to sign off the translation.

You may have had your comparison now, but Hold on!

Back to Emily in Paris the girl who traveled to Paris and she doesn’t speak French. She was fully dependent on MT Tools, in the beginning, the tool was doing just fine. But later on when she wanted to write a letter to her French friend Camile to say “I am Sorry” her message got lost in translation. MT tools can’t convey Feelings!

So, When to use MT tools?

As we mentioned before not all texts are MT- friendly. It’s important to know the situation where MT tools can be a good aid to you.

Internal emails and communications

Thanks to MT tools you can send your email in your language and it will be easily and quickly translated into the language of the recipient.

Technical documentation and product instructions

Product instructions are usually written in short-lined segments that could easily be uploaded and translated by the tool.

Online customer service

MT tools enable brands to interact with their customers all over the world, through which they can provide a great customer experience without hiring translators or employees from all over the world

Data analysis

Some types of MT tools can process millions of user-generated comments and provide highly accurate results in a short amount of time. Companies translate millions of customer reviews daily for analysis.

MT can be the smartest time-saving choice here!

Frequently Asked Questions about ” What is Machine Translation and When to Use it?”

Machine translation is a powerful tool that can be used to translate text from one language to another quickly and easily. However, it is important to remember that machine translation is not perfect and can sometimes produce inaccurate or misleading translations. Here are some situations where you should not use machine translation:

When the translation is critical. Machine translation is not reliable enough for use in situations where the translation is critical, such as medical or legal documents. In these cases, it is always best to use a human translator.
When the text is creative or idiomatic. Machine translation struggles to translate creative or idiomatic text, such as poetry, song lyrics, or proverbs. In these cases, the translation will often be inaccurate or nonsensical.
When the text is culturally sensitive. Machine translation can sometimes produce translations that are insensitive to the target culture. For example, a machine translation of a joke might not be funny in the target language, or a machine translation of a political speech might offend the target audience.
When the text is long or complex. Machine translation is more accurate for short, simple texts. For long or complex texts, it is often better to use a human translator.

The three main techniques used for machine translation are:

Rule-based machine translation (RBMT) uses a set of grammar rules to translate text from one language to another. This technique is often used for technical translations, as it can be very precise. However, it can be difficult to create rules for all possible language pairs, and RBMT systems can be slow.
Statistical machine translation (SMT) uses statistical analysis of bilingual text to learn the most likely translation for a given word or phrase. This technique is often used for general-purpose translations, as it can be more accurate than RBMT. However, SMT systems can still produce errors, especially for complex or idiomatic language.
Neural machine translation (NMT) uses deep learning to learn the translation of text from one language to another. This technique is the most recent and advanced machine translation technique, and it can produce translations that are indistinguishable from human translations. However, NMT systems can be computationally expensive, and they require a large amount of training data.

In recent years, there has been a growing trend toward using neural machine translation for machine translation. Neural machine translation is a type of statistical machine translation that uses artificial neural networks to learn how to translate text. Neural machine translation has been shown to be more accurate than traditional statistical machine translation, and it is also more consistent. However, neural machine translation is still under development, and it can be less accurate for translating certain types of text, such as technical or legal documents.

So, which type of machine translation is typically used? The answer depends on the specific needs of the translation project. For projects that require high accuracy, rule-based machine translation may be the best option. For projects that require speed and consistency, statistical machine translation may be a better choice. And for projects that require the latest technology, neural machine translation may be the best option.

Conclusion

Next time you are having a text you wish to translate, just don’t be Emily!

Make sure to be smart when using the machine translation and use the appropriate tool to help you get the best results.

If you feel that you won’t be able to translate your document properly, you can contact us at Africa Localize. We offer high-quality translation services that will ensure your message is conveyed accurately and effectively.