How to make the most of AI-based translation: pros and cons

The basis of any effective strategy whose objective is to internationalize a business is communication. Suppliers, distributors and potential customers increasingly look for information in their own language in order to feel more comfortable and valued when it comes to forming productive business relations.

To overcome the cultural barrier in business, companies must take into account numerous aspects, including the cultural and linguistic features of each place and sector. Therefore, business translation is a complex challenge that requires extensive resources. 

 

What does AI-based translation mean?

AI-based translation uses digital artificial intelligence tools in order to translate not only written or spoken words, but also the meaning and feeling of the messages. Its main goal is to make global information accessible to everyone, regardless of language or place of birth. 

This technology resulted in a key breakthrough for new intelligent translation systems: neural machine translation (NMT). It is a new approach to machine translation that is much more accurate and sophisticated, with machines learning to translate through a large neural network consisting of multiple processing devices modeled to mimic the human brain.

 

How does AI-based translation work?

The process of AI-based translation begins with data cleansing and training sector-specific systems. Then, through the use of natural language processing (NLP), AI is capable of converting human language into machine-understandable language, which, in turn, allows these systems to convert data from unstructured text into significant data.

AI-based translation is designed to continuously improve the result generated from the data over time. This is achieved through machine learning (ML), a key concept in the field of AI since its beginning, as this process employs computer algorithms that automatically improve the quality of the results as they learn from the information provided by the data.

Its use can be summarized in two main functions. On the one hand, machine learning can be used as a stand-alone tool for large-scale translation. On the other hand, it can be used as a tool for helping human translators, enabling them to increase their productivity and daily production and make the translation process more efficient.






The advantages of AI-based translation

 

Ensuring consistency and the communicative tone of texts 

AI automates translations that are consistent with each client and with the context of the translation assignment and the business. In developing more and more accurate algorithms, AI greatly increases the accuracy of its translation and, in many cases, achieves the same results as human translators.

 

Feedback for continuous improvement

Neural machine translation’s AI-driven engines can be continuously trained by means of human feedback using clients' own content or even examples of other translations or linguistic assets. Thanks to these workflows, machine translation results are getting more accurate and the quality is much higher.

 

Using specific vocabulary 

Advanced AI editors provide terminology databases that allow you to manage terminology more efficiently by organizing terms with customizable meta-information. In this way, users can import terminology with metafields or add new fields, increasing translations’ concordance and specificity, especially in technical texts and specialized content.

 

Saving time and money 

As AI-driven translation improves and learns, the task of machine translation post-editing becomes easier, meaning the costs and time required by human translators are greatly reduced. Therefore, companies with limited resources also have the opportunity to provide a personalized global experience.

 

The limitations of AI-based translation

 

Attention to confidentiality 

By using free online tools, there is a risk that sensitive private data may be exposed, as the open cloud currently still presents problems when it comes to protecting real-time enabled data. The use of a trusted platform with anonymization services and a robust data protection body is the only effective way to address the confidentiality challenge that companies face in multilingual business.

 

Reliance on human translators

Certain types of texts will always depend on human reviewing if companies want to ensure translation quality. It is unlikely, for example, that AI could rival a human translator in the translation and transcreation of emotive, impactful and persuasive texts, like the type of text that is needed in marketing, advertising or risk communications. For this reason, we recommend that human translators review and edit AI-based translations.

 

Initial preparation and dedication

If they are looking for high-quality results, companies need to invest time in preparing and nurturing AI tools from the ground up. Examples include the creation of memory banks or terminology bases for elements commonly used in a specific sector. AI is not magic, although it may sometimes seem like it, so giving machine translation systems the information they need to learn will result in great time and cost saving in the long term.



 

The future of artificial intelligence in language translation

Due to the state of the systems’ evolution, including the lack of transparency in deep learning (DL), very few companies currently use AI-driven translation exclusively.

However, there is no doubt that this technology is here to stay. Artificial intelligence is, and will continue to be, the foundation of hybrid translation models, which allow us to obtain ever more perfect translations by combining AI technologies with human translation.

Over time, AI-based translation, as well as becoming even more accessible, will allow clients and linguists to interact more efficiently. It will therefore become a customized solution that will encourage human-machine collaboration to make the most of the limited time and resources of a skilled human translator.

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