The Future of Website Translation in Light of AI

The website translation industry is constantly evolving to make quality translation accessible to companies of all sizes. The next phase of innovation in the website translation space is set to increase automated AI at scale. The translation industry has come a long way since the days of manually translating texts by hand. The rise of AI-powered translation tools has transformed the industry, making it faster, more accurate, and more cost-effective.  

What is the future of the website translation industry and how are smart tools like AI transforming our approach and helping us reduce overall costs? 

AI in Translation 

The website translation industry has evolved significantly in recent years, thanks to advancements in technology. AI is changing the website translation industry by providing a faster, more cost-effective, and customizable solution for businesses looking to take on a translation or Website-Lokalisierung project. 

AI and machine translation are revolutionizing website translation by automating many of the manual processes involved in website localization. AI-powered translation tools can analyze large volumes of text and accurately translate content into multiple languages. These tools also use machine learning algorithms to learn from their mistakes and improve their accuracy over time. This means that website translation can be done faster and more efficiently, which is particularly useful for businesses with large volumes of content to translate. 

NMTs 

Neural Machine Translation (NMT) is a form of machine translation that uses artificial neural networks to translate text. Unlike traditional machine translation, which relies on rules-based systems, NMT can learn from large amounts of data and improve its accuracy over time. NMT is capable of producing high-quality translations that are almost on par with human translations, making it an increasingly popular technology in the website translation industry. 

The process of building a high quality NMT has two steps:  

• Establish a base "Generic" model for the language pairing. This involves either building and training it from scratch or using a pre-trained model.  
• Your next step is domain-adaptation. This means fine-tuning the generic model you created, implementing more specific data training to make it perform better for your specific situation. This allows the NMT to adopt the vernacular of your industry segment and predetermined brand voice. 

Read about how AI tools like ChatGPT are impacting the translation industry 

Translation Quality Score 

Translation quality is an essential factor when it comes to effectively communicating with a global audience. Whether you are a business trying to reach customers in different countries or an individual looking to communicate with people who speak a different language, the quality of your translation can make a significant impact on how your message is received 

How to Ensure Translation Quality: 

MTPE 

Machine Translation Post-Editing (MTPE) is a process in which human translators review and edit machine-translated content to improve its quality. MTPE can significantly reduce the time and cost of the translation process, while still producing high-quality translations. MTPE is particularly useful for businesses that need to translate large volumes of content quickly, such as e-commerce websites. 

Human translation supervision is executed through Machine Translation Post-Editing (MTPE), a hybrid of Machine Translation and traditional human translation. Post-editing follows the Machine Translation process to improve the quality of the translated text. 

Brand-Adapted NMTs 

We discussed NMTs above and outlined how they are designed to ensure that translated content is consistent with previous work. Brand Adapted NMTs are trained specifically from your previous human translations, glossary, and style guide. Proper use of NMTs will continuously improve your model with each new human quality translation added to your translation memory. This process helps ensure adequate translation quality because it relies on content you've approved and used in the past, which was already reviewed by human translators. This also results in quicker turnaround times. 

Brand Adapted NMT translations have been shown to deliver far superior BLEU scores, a measurement of machine translation quality, than translations that did not use an NMT 

Translation Evaluation vs. Translation Estimation 

Translation evaluation and translation estimation are two different approaches to assessing the quality of machine translation output. 

Translation evaluation involves measuring the quality of machine translation output by comparing it to a reference translation produced by a human translator or an expert in the target language. This is typically done using metrics such as BLEU (bilingual evaluation understudy) or METEOR (Metric for Evaluation of Translation with Explicit Ordering), which compare the machine-generated translation to the reference translation based on various factors such as word overlap, fluency, and grammaticality. 

Translation estimation, on the other hand, involves predicting the quality of machine translation output without the need for a reference translation. This can be done by training a machine learning model on a dataset of human translations and their corresponding machine translations, and then using this model to predict the quality of new machine translations based on various linguistic features and other factors. 

In summary, translation evaluation compares machine translation output to a reference translation, while translation estimation predicts the quality of machine translation output based on various linguistic features and other factors. 

Adaptive Translation™ 

Adaptive Translation™ is the future of website translation. MotionPoint's new suite of intelligent tools comes together to limit the need for human intervention, saving you time and money. The goal of Adaptive Translation™ is to allow functions like AI and algorithmic technology to detect and automatically translate your content based on data training and past translations. The machine translation tools make the process quicker, and the reduction of human translation saves you money 

So, what actually makes up Adaptive Translation™? Here's a breakdown: 

1. Translation Memory (TM)

Translation Memory (TM) is a technology that stores previously translated content and reuses it to improve the efficiency of the translation process. TM allows translators to quickly and accurately translate new content by suggesting translations based on previously translated content. TM is particularly useful for businesses that have a lot of repetitive content, such as product descriptions or terms and conditions.

2. Artificial Intelligence 

AI translation, also known as machine translation, is the use of artificial intelligence and natural language processing technologies to automatically translate text from one language to another. AI translation systems analyze large amounts of data to learn patterns in language usage and syntax and use this information to generate translations. 

Recent advances in deep learning have led to the development of neural machine translation (NMT), which uses neural networks to learn the mapping between languages. NMT has become the dominant approach to AI translation in recent years, producing more accurate and fluent translations than previous methods. 

MotionPoint offers you the choice between a Generic NMT or a Brand Adapted NMT. A Generic NMT does not have the same data training features as a Brand Adapted on, and thus is cheaper and does not put out the same level of quality. 

3. Algorithmic Translation 

Unlike AI translation, which aims to fully automate the translation process, algorithmic translation is a form of human-assisted translation. Algorithmic translation tools can help translators in a variety of ways, such as by suggesting translations for individual words or phrases, identifying potential errors or inconsistencies in the translation, and automatically formatting and organizing the translated text.  

Some algorithmic translation tools can also help manage translation projects, such as by tracking progress, managing glossaries and translation memories, and facilitating collaboration between translators. 

Don’t Fall Behind 

The website translation industry is constantly evolving, and businesses that want to stay ahead of the competition need to embrace the latest innovations in website translation. By using cutting-edge technology and working with experienced translators, businesses can create high-quality, localized websites that resonate with customers around the world. 

MotionPoint is on the cutting edge of the translation industry. By offering the latest and greatest in tech, we can provide top-quality translations while saving you up to 60% on human translation. By staying ahead of the curve and always making the experience better for our customers, MotionPoint is keeping up with the future of the translation industry. 

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