What is Generative AI?
Generative artificial intelligence (AI) refers to a type of AI designed to create new content, such as text, images, or code, based on the input it receives. Unlike traditional AI models, which primarily analyze and process existing information to classify, predict or recommend, Generative AI produces output that may appear original by synthesizing patterns, structures, and relationships learned from vast datasets.
Large Language Models (LLMs) are a subset of Generative AI which are trained on vast amounts of data to specifically understand and generate human-like text. They can perform a variety of tasks, including translation, text summarization, sentiment analysis and conversation. In translation and localization, Generative AI, through LLMs, is transforming how content is created, translated and adapted across languages and cultures. Not only does it enhance productivity and translation quality, but it also enables new, creative solutions that were previously unimaginable.
How has the evolution of Generative AI impacted translation?
Early Linguistic AI applications in translation (such as machine translation) relied on rule-based systems and statistical methods. Modern advancements, however, are driven by neural networks and deep learning. An example of this shift is Neural Machine Translation (NMT), which marked a significant leap forward by enabling AI to understand entire sentences and their context, resulting in more fluent translations. While NMT improves translation quality, Generative AI now takes this a step further by enabling more nuanced and creative text generation.
The development of transformer architectures, such as GPT, has allowed translation systems to better understand and generate content by moving beyond direct word-for-word translation. These models consider entire sentence structures, capturing the meaning behind the text rather than simply translating individual words. This results in more fluent, accurate translations that feel natural and culturally appropriate to the reader.
Fine-tuning has further advanced Generative AI translation models. By training on industry-specific datasets - such as those from legal, medical, or technical domains - these models can be tailored to meet the unique needs of various sectors. Additionally, fine-tuning for individual companies allows for the integration of brand-specific terminology, names and style guidelines. These tailored adjustments significantly enhance the accuracy and relevance of translations, making Generative AI an indispensable tool for producing high-quality, specialized content.
How is Generative AI transforming localization?
Generative AI, through LLMs, has opened the door to several cutting-edge applications in translation and localization. Here are some examples of how these capabilities are being utilized:
- Generating contextualized translations: Generative AI uses context-aware language models to act as an automatic translation provider, producing translations that feel human-like, capturing the subtleties of tone, style, and meaning across languages.
- Utilizing linguistic data for higher-quality translations: By integrating generative AI with translation memories (TMs) and terminology databases, translation output can be produced that aligns with past translations and specific terminology, boosting consistency and quality. This hybrid approach is a form of Retrieval-augmented generation (RAG).
- Automated post-editing and quality assessment: After machine translations are generated, AI models can help assess and improve translation quality. Automated quality scoring can help translators identify where to focus their post-editing efforts, while automated post-editing can automatically refine and improve the text, reducing the need for extensive human post-editing.
- Speech-to-text and transcription: Generative AI can convert spoken language into text, making it easier to translate audio or video content for multilingual audiences.
- Content adaptation for different markets: Generative AI can adjust content to resonate with different cultural and regional audiences by understanding local preferences, colloquialisms, and cultural nuances.
- Creative content transcreation: Generative AI enables the adaptation of marketing slogans, taglines, and creative copy to maintain emotional impact, cultural relevance, and brand voice across languages and regions.
- Automating content creation and instant localization: Generative AI can automatically create content and instantly localize it based on specific purposes. For example, in a customer support scenario, generative AI can analyze a customer’s question in a chat, understand the intent, and respond in the appropriate local language, adapting the tone and context to ensure the reply resonates with the target audience.
- Automated content creation for multilingual SEO: Generative AI enables businesses to automatically generate SEO-optimized content in multiple languages. It can seamlessly incorporate relevant keywords, meta descriptions, and other SEO elements, ensuring content is tailored for search engines. This helps businesses reach wider audiences, improve search rankings, and effectively engage customers across different markets.
What are the business benefits of using Generative AI in translation?
Generative AI offers significant advantages to translation professionals and businesses involved in translation and localization. Some key benefits include:
- Enhancing translation quality: Generative AI can produce more fluent, contextually accurate translations by understanding sentence structures, tone, and nuances. This results in translations that feel more natural and culturally relevant, enhancing the overall quality of content across languages. Combined with human review, you can deliver higher-quality translations that align with brand voice and tone.
- Expanding translation capacity: Generative AI can effortlessly manage large volumes of content across multiple languages, enabling you to translate more without significantly increasing your human resources. This makes it easier to maintain a consistent global presence and keep up with growing content demands across languages.
- Reducing costs and time to market: Generative AI can reduce the need for extensive manual translation and post-editing, cutting down on labor costs and revision time, allowing businesses to launch products and content in multiple languages more quickly.
- Improving personalization and customization: Generative AI can be used to tailor translations to align with brand voice, tone, or specific audience preferences, allowing translation professionals to deliver a consistent message across markets.
What is generative translation?
- In Trados Team, Accelerate and Enterprise (with the AI Essentials add-on): As a feature, project managers can leverage Generative Translation to better prepare files for localization, reducing project turnaround times and enhancing translation quality. Here, Generative Translation leverages any terminology and translation memories applied to the project to customize output. With high-quality results generated from the start, there is less need for post-editing, reducing translation costs and speeding up time-to-market.
- In Trados Studio: Within the desktop editor, translators can access generative translation through AI Assistant. With this feature, terminology is automatically applied and results are applied on a segment-by-segment basis, allowing translators to refine their translation in real time. This provides flexibility and allows for a more customized approach as translators work through their projects.
