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A complete guide to AI localization

A complete guide on AI localization


Artificial intelligence has made a significant impact in the field of translation and localization. Thanks to AI, localization is no longer a tedious and error-prone process. As such, the digital marketplace is quite competitive and 9 out of 10 customers are only interested if the product or service information is available in a language of their choice. Therefore localization is very crucial for the success of your business in a digital marketplace and the use of AI can improve consistency and speed up the process.

In this blog, let us explore more about AI localization and how it can positively impact your business

What is the role of AI in localization?

AI localization is the perfect combination of artificial intelligence and the localization process, which can improve efficiency and accuracy while also positively influencing the localization workflow. AI systems can produce refined translation outputs while also speeding up the review and project management process. AI localization is a data-driven process that utilizes translation memories, glossaries, and feedback loops. Therefore the translation output is of human quality and contextually appropriate.

With the help of AI-driven tools, you can automate repetitive tasks, optimize workflows, and provide predictive analysis that will help you make informed decisions. With the help of AI technology, localization becomes faster and cost-effective and reduces the time to market for your digital assets.

Also read: How to use ChatGPT for translation

Subfields of AI used in localization

The three subfields of AI  that are used in localization include machine learning, deep learning, and natural language processing.

Machine learning

Machine learning is a subset of artificial intelligence that develops algorithms based on data and uses them to train computer systems to make predictions. There are three main techniques in machine learning such as

  • Supervised learning
  • Unsupervised learning and
  • Reinforcement learning

Machine learning enables computer systems to adapt to specific languages, dialects, and cultural nuances. With machine learning, you can automate the entire localization process and make it more efficient and cost-effective.

Deep learning

Deep learning is a subset of AI that refers to processing large amounts of data via neural networks, identifying patterns, making predictions, and taking actions based on that analysis. It mimics the ability of the human brain to learn and make decisions. One of the main applications of deep neural networks is neural machine translation. Using deep learning techniques, the text, audio, and video content can be analyzed to determine the language used. By learning from vast data sets, the deep learning models can enable systems to improve their localization capabilities to a greater extent.

Natural language processing

Natural language processing (NLP) is a subset of AI that refers to the capability of computers to understand, interpret, and generate human language. This is done using techniques like text analysis, sentiment analysis, language translation, and speech recognition. Using NLP algorithms, tailored outputs can be generated by analyzing the target language’s linguistic patterns, idiomatic expressions, and cultural nuances.NLP techniques automate the translation process and generate contextually appropriate outputs across various linguistic contexts.

Difference between AI localization and traditional translation.

The traditional translation is generally performed by human linguists and is a time-consuming process. AI localization employs automated systems that complete all tasks with greater speed and efficiency. In a human translation, there is always a challenge in maintaining consistency in outputs. When multiple translators are involved in a project, the consistency of the output can be impaired. With AI localization, output consistency can be easily maintained across the content irrespective of the volume. Human translation incurs a higher cost due to the manpower. AI localization is highly cost-effective and needs minimal human intervention. Scalability can be challenging when a translation project grows and includes multiple languages. Larger projects with multiple languages can be managed more efficiently using AI-based systems.  The translation tools based on AI can be seamlessly integrated with other software, and streamline the entire translation workflow.

Importance of AI localization in business

Localization techniques that are powered by artificial intelligent tools have multiple benefits. To begin with, it is the most efficient and cost-effective means to localize your digital assets and it saves your time and resources to a greater extent. AI-powered localization tools can also provide meaningful insights into user experiences and behaviors by analyzing language-specific data. This will enable management to make data-driven and informed decisions. AI localization tools provide clear communication to end users while also reducing language-related misconceptions and misunderstandings. With this localization method, you can provide the users with an enhanced experience and increased customer satisfaction. By breaking down the language barrier through localization, you can expand your market reach. It also improves brand perception and loyalty.

Also read: Use of ChatGPT in localization

Best practices in localization

While artificial intelligence can automate translation tasks and produce high-quality results, it cannot replace the in-depth knowledge and cultural insights provided by humans in localization efforts. As a result, to create high-quality localized content, it is important to strike a balance between technological and human expertise. Localization is an ongoing process. It is important to review and fine-tune your localization strategies from time to time so that your efforts remain successful and relevant. There are many AI-powered localization tools on the market right now. You must make an informed choice as to which tool would suit your localization requirements, is scalable, and can be seamlessly integrated with your existing systems. Finally, there should be a clear objective behind every localization effort. Using your AI tools in alignment with your objectives will allow you to reap far greater benefits from localization.

How do you plan your AI localization strategy?

Crafting a robust AI localization strategy requires proper planning and consideration of various factors to ensure optimal results. To begin with, conduct a thorough assessment of your localization need and take into account parameters like

  • The ability to provide accurate and consistent outputs
  • Has a robust content management system
  • Can be customized based on your business needs
  • Offers high security
  • Seamless integration capabilities with your existing systems

MoxVeda from Process Nine Technologies is an AI-based language localization platform that can localize your website, mobile applications, etc that can be effectively integrated with your systems. MoxVeda is compatible with all the CMS platforms and handles all major tech stacks. It is highly secured and can handle both dynamic and static content of your digital assets and generate high-quality outputs. Moxveda also gives you the liberty to choose your translation sources (machine or human), target languages, and terms based on your business needs.

Are you looking for a reliable partner to carve out your localization strategy or take your existing localization efforts to the next level? Contact us today!!