Machine Translation Decoded

An automated system that allows for the translation of all types of content without human intervention is called machine translation (MT). It is a language translation done entirely by a computer or machine. Machine translation is not a new phenomenon. However, technology has advanced so much in recent years that machines can now translate entire languages independently. Machine translation differs from computer-aided translation (CAT) in that human input doesn’t have to be relied upon to come up with a translation. Read on to decode this cutting-edge and versatile new aspect of language translation.

Machine Translation (MT) Types:

Rule-based Machine Translation (RBMT)

- words and sentences are translated by the translation engine based on rules that the user can adjust.

Statistical Machine Translation (SMT)

- The system translates based on a large body of parallel texts (a corpus) that the translation engine has been trained on.

Neural Machine Translation (NMT) 

- The engine is AI-powered and can mimic how a human brain works when processing language.

- NMT engines can understand entire sentences and even paragraphs at once instead of translating word by word, thanks to machine learning

Raw or Post-edited?

Depending on their goals and needs, businesses and companies can choose whether to use raw (unedited) machine translation or hire human translators to refine the translation output. The refining of the translation output through human input is called machine translation post-editing (MTPE), and it can be either light or full. In addition, different types of texts and content require different levels of editing. For sample, a website’s communication details page may need light editing; yet, a press release that straight marks the brand’s importance should go via a full post-editing strategy. Human translators should always handle sensitive content such as financial statements by the same logic. 

Machine translation output quality varies depending on the following factors:

● The language pair at hand - languages of different syntactic structures such as German and Tuyuca may be harder to accurately translate compared to languages with similar syntactic structures, such as Italian and Spanish.

● The subject matter of the original text - general-language documents tend to translate more accurately than legal texts, for example.

● Whether the source text undergoes pre-editing to eliminate certain elements may cause the translation engine to struggle.

● The project’s scope and the amount of data available for training the engine.

● The usage of editing resources or human translators to purify the translation result.

● The provider - some translation engines perform better than others due to having access to more data.

Thanks to contemporary technology, it’s also possible to identify the quality of machine translation output to focus on post-editing resources where they are most necessary. Identifying the quality of machine translation output is called machine translation quality estimation (MTQE).

Some Important Machine Translation (MT) Reminders

1.  Please exit it in the hands of human translators whenever the leading rate is key, and there are no financial or time rules. Accuracy, consistency, and quality are especially important in document translation services and highly creative projects designed to incite action.

2.  For low-impact, non-specific content, raw machine translation is best. Examples of such content include user-generated content like product reviews, customer inquiries, or frequently amended content like feature and information updates.

3.  Apply a light or full MTPE when your brand may suffer due to inaccuracies. Familiar inaccuracy cases contain product titles and descriptions (they manage to contain valid names & polysemous words), and press releases.

4.  For raw machine translation, it’s important to utilize a state-of-the-art MT engine that is admiringly trained & powered by AI technology.

Author bio: Angelo Castelda who is a freelance a writer from Asia. Besides writing, he even spends his valuable time traveling & understanding diverse cultures & languages, which spread his heart additional to knowledge and impart wisdom concerning language translation.