The CSA Research reported that around 55% of international users only buy from websites that provide information in their native language. Many companies that plan to widen their target audience and expand internationally have begun to localize their content.
The problem with content localization is that it may take time to create them. But with the recent development of neural machine translation, it could be used to speed up the content localization process.
If you want to learn more about how to use it effectively, keep reading!
What is Neural Machine Translation? What is it for?
Recent technological development has led to the creation of Neural Machine Translation (NMT). NMT has neural networks that utilize artificial intelligence to translate text. Neural networks are made of neurons that allow the machine translation to learn and interpret the languages it comes into contact with.
What is NMT used for? It has been used for a niche-specific content, like medicine and law. Many experts have estimated that the accuracy rates are 70% to 90% for Neural Machine Translation. The translation quality will depend on factors like the size and complexity of the dataset used for training, the decoding algorithm, and the attention mechanism used by the systems in identifying parts of the source text.
Some marketers have seen the potential of NMT in creating localized content. It would allow them to create multilingual content more efficiently, targeting several different markets. However, some are still wary that one could make creative content from machine learning translation.
After all, translation is a combination and science and art. It requires excellent attention to detail, and the process itself heavily relies on the cultural and linguistic aspects of the source and target language.
Creativity in NMT: Is it Possible?
At this moment, no machine can truly replace the human mind regarding creativity. Like with any technology, neural network translation is only a tool. So when marketers plan to implement content localization, they will still need localization experts specializing in content marketing to get the desired results.
When discussing on how to localize content? It all comes down to your intent and objective for localizing content. Content localization is adapting content based on your target audience’s cultural and linguistic preferences.
Besides producing large volumes of translations, neural machine translation allows businesses to communicate regardless of language barriers by identifying key phrases and terms for market research, creating sentiment analysis and surveys, and having it specialized for content marketing. You can use free NMT engines, like Google Translate and DeepL, as long as you have a neural machine translator to ensure the output’s quality.
Creativity is subjective. Because of this, how a localized content will be received by its target audience will depend on the multilingual content marketing specialist skill, market factors, and the timing. There’s no exact formula but there is a process and it’s by this process neural translations play a significant role.
How Companies Use NMT in Their Localized Content Creation Process
It’s not enough to change the content’s language to another. There’s a step-by-step process involved in it, as follows:
- Extracting the Content – This step involves developing a detailed inventory of your content and creating a glossary before finally extracting it to be examined by a localization specialist.
- Content Localization – With your neural machine translator and localization specialist, they will have the extracted content translated by an NMT and then transformed to suit the target market’s preferences.
- Have a Quality Assurance Team – Don’t rush this phase. It’s crucial that during this period, you catch all the errors before you launch or publish localized content. It’s good to have another group handle this stage to provide new insight or perspective in identifying any mistakes to have it fixed and edited.
- Launching of the Localized Content – After you’re confident in your localized content’s quality, you can deploy it.
- Implementing Content into Your Strategies – Before you do content localization, you must conduct market research ahead of time. It’s to ensure that whatever content you create, you can quickly implement it into your strategies. For example, you’re looking to localize your website. You will need to consider the technical aspects, like multilingual SEO, preparing your website for localization, etc.
- Testing, Retesting, and Adjusting – With the global market’s competitiveness, you must keep up by tracking and measuring the results. One way of going about this is by having your content tested and retested quite often to have it fine-tuned for your target audience.
What You Should Avoid
While researching this topic, we listed a couple of considerations you should make when using NMT, as follows:
1. Forgetting to consistently train NMT engines
NMT engines require constant feeding and fine-tuning of data. It’s problematic if the NMT system is only being trained with small, simple datasets, as it lowers the accuracy of your output. You must have it updated by feeding it constantly with large quantities of a complex dataset, allowing the system to improve.
2. Failing to create a team
Because you will need to consistently train an NMT engine, it’s essential to have a team of translators and quality assurance specialists managing it. They will monitor the progress of your NMT engines and ensure that the neural network translations are up to standards, having a team of experts who have the experience and training is essential as they will be the ones to ensure that everything runs smoothly.
3. Not simplifying source text before translating
Machine learning translation, like any tool, will function more efficiently if they are handed simplified source text data. It helps with the alignment and makes it more accurate. The longer the sentence structure, the more likely the quality of the translations will be lower. Suppose you can edit beforehand the original text and make it simplified, the better.
4. Ensuring translations are for the proper domains
NMT can be tailored for specific industries compared to previous machine translation engines. However, there are drawbacks. For example, you used an NMT engine for a previous project related to digital marketing and content creation. After a couple of days, you tried using it to translate documents for business purposes.
It is a mishandling of an NMT engine, as these are two entirely different domains with their own rules and expectations regarding translation and language. You will have to consistently have your neural machine translator feed the NMT engines with data to ensure it’s specialized to a domain. Having the NMT engine translate a text outside its domain defeats the whole purpose of cultivating data for an NMT engine.
Final Thoughts
Neural machine translation is a relatively new technology, but it has garnered wide attention in the language industry and other fields. For marketers, it has allowed them to do content localization much quicker, like localizing websites and apps, blog articles, PRs, etc. Hopefully, the tips and advice in this article will get you started using machine-learning language translations.