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GenAI is going to reshape your localization workflow

Global organizations worldwide recognize that to reach audiences and build meaningful connections, they can’t rely on content designed for their primary market alone. Tailored, localized content is the key to success.

Understanding Generative AI technologies

GenAI is a multifaceted branch of artificial intelligence with the power to transform many industries, localization being a prime example. The core principle is this:

GenAI algorithms⁠

analyze and learn from massive amounts of existing data.

Under the hood, GenAI uses artificial neural networks. In fact, the architecture of these networks is very similar to what we have seen before in Neural Machine Translation. Neural networks essentially perform two kinds of operations: encoding and decoding. Encoding is the process of “understanding” input data and the patterns found in it. Decoding, on the other hand, is the generation of content that follows patterns encoded in the data.

That data could be text, images, code, or other content types. The trained algorithm can then generate new, similar content while adhering to its learned patterns and style. Let’s look at

specific GenAI approaches⁠

that have a profound impact on the localization:

Machine translation advancements

⁠

Machine translation⁠

is certainly not a new concept, but GenAI is reshaping its capabilities.

Traditional systems relied heavily on rules and linguistic analysis. Neural Machine Translation, fueled by large language models, changes the game.

NMT systems are trained on enormous volumes of human-translated text datasets. This allows them to gain an impressive grasp of context, natural-sounding word choices, and the nuances of human language.

The use of LLMs and zero-shot learning results in translations that are significantly smoother, requiring less post-editing by human translators and saving substantial time and effort compared to the months or years typically needed for MT training.

It is also possible to alter the translations automatically by requesting the large language model to generate text in a different mood or formality level.

Image and multimedia localization

Communicating effectively across cultures requires more than just translating the words. Images, videos, and other multimedia assets carry messages and evoke feelings that might not translate directly. GenAI-powered tools are emerging to address this challenge.

From detecting and replacing text embedded in images to recognizing potentially sensitive cultural symbols, these tools aid in the process of making visuals more suitable for a target audience. Some tools even suggest entirely new images that better align with a specific market’s norms or preferences. Some examples of this approach include using native actors for specific countries with different physical features, and making sure that cultural nuances are preserved when communicating to those audiences.

How GenAI augments the MT process

To gain a deeper understanding of how

GenAI⁠

is revolutionizing localization, let’s examine its impact on machine translation:

Data understanding: GenAI systems excel at analyzing the source text with impressive nuance. They go beyond isolated words, examining sentence structure, overall meaning, and contextual clues.

Recognizing structures and patterns: With training on extensive language datasets, these systems develop a strong understanding of how different languages are structured. This lets the GenAI replicate those patterns for more fluent translations.

Generating multiple options: GenAI can often provide several plausible translation choices. It then utilizes its understanding of probability to rank the most likely accurate and fitting translations. This provides localization teams with flexibility.

Constant learning: GenAI-powered MT isn’t a one-and-done process. Feeding additional data into the system enables it to continue refining its translation abilities, improving over time.

Understanding idioms and colloquialisms: One area where GenAI-powered MT excels is in recognizing and translating idioms, slang, and cultural references. This capability adds another level of sophistication, as these elements can be particularly tricky for traditional MT systems.

Zero-shot learning vs. traditional MT training: LLMs offer zero-shot learning, allowing them to perform translations with little to no prior specific training. This contrasts with traditional MT systems, which require months or even years of extensive training to achieve high-quality translations.

The possibilities here are exciting for localization professionals. While human expertise remains essential, GenAI acts as a powerful tool for increased efficiency, streamlined workflows, and more impactful global content.

Enhancing the localization workflow with GenAI

⁠

Generative AI⁠

is a practical tool that can streamline and enhance specific stages of the localization process. Let’s explore how GenAI can revolutionize pre-translation, translation, and the broader task of content adaptation:

Pre-translation and content preparation

Because data breaches are a constant threat, safeguarding sensitive information, particularly patient data, is critical. Life science companies must adhere to stringent data protection regulations that other industries do not. Regulations set the bar high for privacy and security, requiring strong measures to protect personal data from unauthorized access.

A suitable TMS for the life science industry must offer comprehensive security features that guarantee data integrity and confidentiality.

Content analysis and identification of repetitive elements: A key efficiency gain lies in preparation for machine translation. GenAI excels at analyzing large volumes of content to identify segments that are highly repetitive. This could include standard product descriptions, disclaimers, or commonly used phrases. By pre-translating these segments and feeding them into a translation memory system, human translators can save time and effort when encountering these phrases again in future content.

Utilizing GenAI for automatic content summarization: When dealing with extensive documents, technical manuals, or other lengthy texts, GenAI tools can generate concise summaries. These summaries can then be translated into multiple languages, giving project managers and localization teams a quick overview of the content. This aids in decision-making regarding translation priorities and resource allocation.

Translation and editing

NMT powered by AI: Neural Machine Translation driven by GenAI provides a significant boost in translation quality. This directly leads to reduced post-editing workloads for human translators. Rather than correcting fundamental grammatical errors or awkward phrasing, translators may only need to make minor adjustments for style or tone, freeing up their time for more complex tasks.

GenAI-assisted terminology management: Consistency in terminology is vital, particularly for brands with specific technical vocabulary. GenAI can enhance terminology management systems in several ways. First, it can suggest context-specific terms based on the rest of the sentence during translation, ensuring the use of correct and consistent terminology. Secondly, GenAI tools can be trained on customized terminology glossaries, further reinforcing brand-specific language within translations.

Content adaptation and transcreation

Culturally relevant variations: GenAI can generate multiple variations of marketing materials, slogans, or website copy. These variations capture the essence of the original message but reframe it with cultural nuances and sensitivities of the target market in mind. Transcreators and copywriters can then use these variations as a springboard, selecting the most effective adaptation.

Adapting content for regional nuances: Even within the same language, regional differences may necessitate content adjustments. A GenAI system trained on data from a specific region can suggest changes in word choice, phrasing, and even humor to better align with local preferences. This helps avoid translations that might sound correct but feel “off” to native speakers in a particular location.

Personalization at scale

Tailored localized content: The ability to personalize content is increasingly important, but doing this at scale across languages is a challenge. GenAI opens up exciting possibilities. It can analyze customer data and preferences within a particular market, and then suggest content variations. For example, a product recommendation on an e-commerce site may be phrased differently based on the customer’s browsing history and location, creating a more bespoke experience.

Important considerations

It’s crucial to remember that

GenAI tools⁠

are most effective when used in collaboration with human expertise. Linguists and/or in-country reviewers (ICRs) bring their invaluable understanding of cultural subtleties, the nuance of brand voice, and the ability to handle particularly complex or creative texts that may require an approach beyond the capabilities of the current generation of AI.

Maintaining quality and human expertise

AI should always act as an aid to humans even if, under some specific circumstances, it does 99% of the work. Nevertheless, certain aspects of effective localization transcend what even the most sophisticated algorithms can independently accomplish.

The role of human translators and localization specialists

Cultural sensitivity

GenAI may produce output that is technically accurate but misses the cultural context. A human translator or localization specialist can identify potential ambiguities, unintended connotations, and subtle cultural references that might be lost in machine translation.

Adaptation of humor or colloquialisms

Humor, slang, and idioms can infuse content with personality. However, translating these elements literally often leads to awkward or confusing results. Human expertise is needed to assess whether humor should be adapted, replaced with a cultural equivalent, or perhaps removed entirely if it doesn’t resonate in the target market. For instance, an English speaker might say “It’s raining cats and dogs” to mean it’s raining heavily, whereas a Spanish speaker would say “Está lloviendo a cántaros” (it’s raining pitchers).

Brand voice consistency

Every brand strives for a unique and recognizable voice. This voice is built on carefully crafted language choices, overall tone, and a style that is more than the sum of its words. While GenAI tools can be trained on brand-specific data, fine-tuning and ensuring that nuanced brand voice remains consistent, particularly with creative materials, requires the insight of a skilled localization professional.

Quality assurance considerations

Implementing GenAI within localization workflows demands rigorous quality control processes:

Establishing clear standards

Teams must determine the level of fluency, accuracy, and cultural appropriateness they require for different content types. These standards act as a benchmark for evaluating GenAI output.

Regularly reviewing and re-training

GenAI models constantly learn and evolve. Teams need a framework for assessing the quality of output over time. This informs if GenAI models need refinement or additional training to maintain consistency and accuracy.

A dedicated QA process

Depending on the project, a separate QA stage, performed by experts who were not involved in the initial translation, may be needed. This adds an extra layer of scrutiny to make sure the final content meets quality standards.

GenAI is incredibly promising, but it’s not a substitute for the knowledge, creativity, and cultural understanding that human experts bring to the localization process. Technology enhances but does not diminish that role.

The future of localization with GenAI

Generative AI is still rapidly developing, and its influence on the localization industry is only beginning to unfold. Let’s explore some emerging trends and possibilities:

Emerging trends

Real-time translation: While not yet perfect, GenAI is pushing the boundaries of what’s possible with real-time translation. Imagine live video calls seamlessly translated with minimal delay, or virtual conferences where attendees can select their preferred language and experience a localized audio experience. This would break down language barriers in unprecedented ways.

Voice localization: Voiceovers and narration for videos or multimedia content involve not just transcribing and translating the text, but also ensuring the chosen voice talent aligns with the target market’s preferences. AI-powered voice generation and adaptation tools have the potential to streamline this process, even allowing for the creation of synthetic voices tailored for specific demographics, regions, or brand personalities.

AI-powered content creation: GenAI isn’t just about transforming existing content. It opens doors for creating multilingual marketing materials from scratch. Imagine tools that help develop campaign concepts, slogans, or ad copy specifically designed to resonate with different cultures, all informed by AI’s vast data analysis capabilities.

Impact on the localization industry

Increased efficiency and cost reduction: GenAI undeniably streamlines many localization tasks, leading to faster turnaround times and potential cost savings. This allows for scaling localization efforts more effectively as companies expand into new markets.

Broader accessibility: By making localization more efficient and potentially more affordable, GenAI plays a role in democratizing content. Companies or organizations that might not have considered extensive localization can now reach wider audiences. This increased access has positive implications for education, information sharing, and cross-cultural exchange.

GenAI is incredibly promising, but it’s not a substitute for the knowledge, creativity, and cultural understanding that human experts bring to the localization process. Technology enhances but does not diminish that role.

What are the key features of a TMS for managing medical terminology?

GenAI doesn’t signal the end of human localization experts. Instead, the focus will shift. Rather than spending the bulk of their time on direct translation, localization professionals will become:

Quality controllers: Their role will center on the careful assessment of the localized content produced by GenAI systems, ensuring cultural authenticity, accuracy, and brand voice consistency.

Creative adaptors: While machines may generate options, the final adaptation for optimal cultural resonance remains in human hands. Localization professionals will apply their creativity to transform GenAI’s suggestions into impactful content.

Tool masters: Understanding the capabilities and limitations of different GenAI systems becomes a core skill. These professionals will be at the forefront of selecting appropriate tools, training models on project-specific data, and integrating the technology effectively into localization workflows.

The future for localization professionals in GenAI is one of constant learning and evolving alongside this groundbreaking technology.

Conclusion

Generative AI is reshaping the localization industry, offering solutions to challenges that have long been part of the process. By streamlining tasks, suggesting adaptations, and taking on repetitive work, GenAI systems offer a powerful toolkit for localization professionals.

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