Content is growing, and what’s more, there’s now a demand for immediacy, as users expect content to be available in their language instantly. With the expectation that mountains of content can be translated within limited budgets – translations are needed quicker than ever before.
Translating vast amounts of content could bring complications around cost, quality and time to market. Technology is becoming increasingly commonplace within translation, in order to remedy some of these potential issues. Advanced translation technology is changing the face of translation – large amounts of content can be translated quickly, at a reduced cost, whilst still maintaining the quality of the final content, through the use of machine translation (MT).
In order to achieve maximum results in machine translation, both in terms of quality and cost, it is essential to write your documentation in clear, coherent, concise and a structurally correct way.
This might sound like a basic rule, but a machine translation engine cannot accurately identify and translate a word that has been spelled incorrectly. Even a human translator would still question the source content, leading to longer turnaround times. Make sure that you proofread your content before sending for translation.
A machine translation engine can recognise repeated phrases throughout a document, and can accurately translate them in a consistent manner. Try to write phrases that can be used several times throughout your documentation, and costs will diminish.
For example, you could use the below phrases within several sections of the same document:
Good example: It is important to eliminate any errors in a document. Proofreading is crucial because proofreading eliminates errors.
Bad example: It is important to remove any mistakes in a document. Proofreading is crucial because proof-reading eliminates errors.
Although advanced technology can handle lengthy sentences, try to keep to the notion that one idea = one sentence. Where possible, break long sentences into two shorter ones. Keep your sentences between 5-25 words, as these are the easiest sentences for a machine to translate. Sentences of less than 5 words though can prove to be problematic, as they are seen to be vague or ambiguous.
Do not over-complicate the structure of your sentences. Ensure that each phrase is complete (begins with a capital letter, has one main clause, and has an ending punctuation).
Good example: Machine translation can play a vital role in your localisation strategy.
Bad example: Your translated copy, as part of your localisation strategy, can be assisted by a machine that plays a vital role; that which we call machine translation.
Get rid of words that do not contribute to the meaning of a sentence, or words that over-complicate the structure.
Good example: He works on marketing projects.
Bad example: He is the man who works on marketing projects.
The active voice is a style of writing that cuts out vagueness and ambiguity. Again, if a human is unsure on the exact meaning of a phrase, then a machine translation engine is going to struggle, especially if your sentence has a double meaning.
Good example: I will always remember my first time using a machine translation engine.
Bad example: My first time using a machine translation engine will always be remembered.
This phrase is vague because it is unclear who will always remember using the machine translation engine; it could be you, someone else, or the world in general.
Try to specify nouns using “the”, as a machine translation engine can struggle to distinguish between verbs and nouns. A lot of short nouns can also be verbs, for example ‘skip’, ‘bank’, ‘lodge’ – these can cause further confusion if used without a definite article. Instructions and user manuals often omit the definite article.
Good example: Build the engine. Train the engine. Use the engine.
Bad example: Build engine. Train engine. Use engine.
A machine translation engine may not convey the correct meaning of colloquial or idiomatic phrases and the meaning may not make sense to international users.
Good example: She didn’t come into the office as she was not feeling well.
Bad example: She didn’t come into the office as she was under the weather.
Keeping the above advice in mind when creating and authoring your content, whether it be e-Learning modules or user guides, will mean improved consistency, lower costs and shorter turnaround times. Find out if your content is appropriate for machine translation – leave your details in the form below.