termbase

5 points on using AI efficiently in your business

30.1.2025 by Delingua

Does your company use AI in content creation? For most companies, this is already part of everyday operations. Read our article for tips on how to ensure that AI tools serve your company’s goals optimally.

A recent survey (Content Marketing Institute, 2024) found that over 50% of companies use generative AI in content creation. AI is widely used to produce website content, email campaigns and various publications, among other things.

While AI delivers speed and efficiency in content creation, it needs to be accurate, brand-aligned, secure and of the highest high quality. How can we ensure that AI-generated content meets these requirements? And what kind of solution does LanguageWire offer?

We listed five points to keep in mind when using AI tools:

1. Is the information based on researched facts?

If the tool you use is not able to leverage your company’s language resources, such as your termbase and translation memory, you should be extra careful regarding the accuracy of the information. “AI hallucinations” refers to a generative AI tool producing incorrect, misleading or completely erroneous information but still presenting it as factually true. This is an unfortunately common phenomenon and even if the tool provides sources, the information can be unreliable.

AI can also expose you to the risk of plagiarism by copying content directly from sources. If the AI tool you are using does not automatically check for content originality, use plagiarism detection tools to scan for copied content.

2. Does the content sound human?

AI-generated text can easily sound robotic and monotonous. For example, the text may use phrases that do not sound natural or too far-fetched expressions that still somehow miss the point. AI does not completely replace creative work or expertise, but it is an excellent tool for creative planning. Not all generative AI output is flawless, so make sure you carefully check the tone, style, and readability of your content and make sure it sounds human.

3. Does the content match my company’s needs?

Generative AI tools can often produce seemingly random results, requiring multiple prompting rounds and extensive manual post-editing. Evaluate whether the AI tool can scale content to your growing business requirements, whether that involves creating different content versions, handling increasing volumes, adapting the content to various formats or translating content into other languages. A user-friendly and intuitive user interface also enhances productivity.

4. Are the style and terminology consistent?

Always make sure your content is consistent and aligned with your brand. We recommend that for business use, you choose an AI tool that automatically generates content that is customised to your business needs. Some AI-powered content creation tools, such as LanguageWire Generate, leverage a company’s own language resources to produce content that is aligned with a brand’s style and terminology. If the tool does not offer this feature, create a list of written brand guidelines, including terminology, and have your content team apply them to all content.

5. How secure is my data?

Unfortunately, not all tools comply with the highest security standards. So always remember to assess the data security and privacy features of the AI tool you use. Tools like LanguageWire Generate keep your data secure with enterprise-grade security, ISO standards, cloud-based infrastructure and compliance with GDPR and CCPA.

Introducing LanguageWire Generate

AI undoubtedly brings efficiency to content creation, but sometimes real success depends on the tool you use. LanguageWire Generate, our AI-powered content creation tool, uses the customer’s own language resources and delivers contextually-adjusted content that aligns with your brand’s style and terminology.

By leveraging state-of-the-art technology and your company’s language resources, LanguageWire Generate minimises content inaccuracies and produces high-quality content tailored to your business needs – without compromising on data security.

Would you like to try LanguageWire Generate and see how it meets your company’s needs? Get in touch and we can tell you more!

The article is based on LanguageWire’s article (Alisdair Mans Cornwell).

AI-powered subtitling, dubbing and interpreting

28.10.2024 by Sofia Väänänen

Video is becoming the dominant form of communication and will transform the way we produce and consume content. Learn more about how video is revolutionising global communication and how AI-powered solutions such as subtitling, dubbing and interpreting can improve global reach.

Data shows that 89% of customers want to see more videos from brands, and 90% say that videos influence their buying decisions. Videos help consumers visualise and simplify purchasing processes and understand the different features of products and services, increasing their confidence in making choices. (The State of Video, HubSpot 2024)

But is video more than just advertising? Yes, it is! Video is a powerful tool for creating engaging content that catches the eye, but it also provides a great solution for simplifying complex subjects and introducing new processes. Video can be used for things such as internal communications, onboarding and training – you name it.

Video is here to stay – how can LanguageWire help?

Today’s fast-paced communication environment requires adaptability. It is evident that video is becoming the dominant form of communication and will change the way we produce and consume content. But the best part? You don’t have to navigate this shift alone!

Let us walk you through three of our AI-powered video solutions that can increase efficiency and break down language barriers to reach a broader, global audience.

Solution 1: AI-powered subtitling

Studies show that 85% of people watch social media videos on mute. Unfortunately, this often leads to videos losing their meaning when a lot of information is missed. Media consumption is booming, and the flood of information is huge – how do we stand out?

That’s where LanguageWire‘s unique value proposition comes in: AI-powered, human-refined subtitling solutions that blend together the best of two worlds. They seamlessly localise video content across multiple languages and diverse audiences, whilst maintaining accuracy, quality and brand consistency.

Our Smart Editor offers an innovative approach to subtitling. It simplifies complex video localisation workflows for global enterprises and combines the best of AI and human expertise to generate high-quality, contextually accurate subtitles. Smart Editor integrates with your existing linguistic assets, like Translation Memories and Termbases, and ensures that your subtitles use the correct terminology and tone throughout the video.

Learn more about our AI-powered subtitling solutions.

Solution 2: AI dubbing

If you want your video to reach every potential customer, you have to speak their language. Due to increasing demand for multilingual content, the AI dubbing market is expected to grow exponentially in the upcoming years.

AI dubbing is the automatic translation and replacement of spoken audio with synthetic voices in other languages. AI dubbing uses technology like machine learning, speech recognition and AI voice generation to create a voiceover that matches the timing, tone and message of the source video. The content is reviewed by our experts and post-edited to ensure quality and accuracy.

AI dubbing eliminates language barriers and makes content more accessible, engaging and personalised. For brands, this means faster and more affordable localised content with a consistent brand voice.

Solution 3: AI interpreting

The demand for remote interpreting solutions has increased significantly in recent years, and studies show that AI-related services, including AI interpreting, are expected to expand massively. The AI remote work market is set to grow annually by 18% from 2024 to 2033 (Slator interpreting report, 2024).

AI interpreting, also known as AI speech translation, is a technology that provides a fully automated and real-time translation of live speech. From speech, AI interpreting starts with automatic speech recognition, moving into speech-to-text and machine translation, and then finally into speech synthesis.

Thanks to hybrid and remote solutions, interpreting is easy and affordable and can effectively reach participants across geographical boundaries. AI-powered interpreting opens the doors to a multilingual audience and offers flexible solutions tailored to the customer’s needs, according to the type of event, budget and schedule.

Let us help you take the first step!

AI is breaking barriers for multilingual content production and the shift from text-to-video isn’t just the future – it is happening as we speak.

The difference between a termbase and a translation memory

18.10.2024 by Delingua

If your business regularly works with translations involving multiple languages, you may have already encountered the terms “termbase” and “translation memory”. While both are essential tools for translators, they each serve a different purpose.

In this straightforward guide, we’ll explain the basics of termbases and translation memories, the differences between the two, and how they can help to improve your translations.

What is a termbase?

A termbase (TB), also known as a terminology database, is a collection of specific words and expressions used in a particular subject area, industry, or company. A term entry may include definitions, examples as well as the corresponding translations of these words and expressions in other languages. The primary purpose of a termbase is to ensure consistency and accuracy in translations by providing a reference for the translator.

For example, when translating a legal document, the corresponding termbase might include terms like “jurisdiction,” “liability,” or “indemnity.” When translating a marketing brochure for a technology company, on the other hand, it may include terms like “cloud computing,” “cybersecurity,” or “digital transformation.”

What is a translation memory?

A translation memory (TM) is a database that stores previously translated content in the source and target language. The content is stored as bilingual segments – or translation units – in the database for future use. When a translator encounters the same or a similar sentence or string in a new translation, the translation memory will provide the previously translated version as a suggestion for the translation, saving time and improving consistency.

For example, if while translating the user manual for a product, the sentence “Press the red button to start the machine” has already been translated, the translation memory will provide the stored translation as a translation suggestion for a new sentence like “Press the green button to activate the machine.”

How do they differ?

While both termbases and translation memories are databases used in translation, they serve different purposes. A termbase is a reference tool used to ensure consistency in terminology across translations, whereas the purpose of a translation memory is to reuse previous translations and thereby save time.

How do they work together?

Termbases and translation memories work together to improve the quality and efficiency of translations. For example, a termbase can be integrated into computer-assisted translation software to ensure consistent terminology across translations, improving the accuracy of the translation memory suggestions.

How can they benefit your business?

Using a termbase and translation memories can benefit your business in several ways. By ensuring consistent use of terminology, you can improve the accuracy of your translations, making your content easier to understand for your target audience. Additionally, by reusing previous translations, you can save time and reduce translation costs.

Using these tools can also help you maintain brand consistency across languages, strengthening your corporate voice and ensuring that your messaging is clear and effective in every language. This can improve customer satisfaction.

Want to know more about our advanced solutions for termbase management and translation memories? Reach out to us and we will be in touch shortly.

This article was originally published by LanguageWire Company (Verity Hartley).

LanguageWire Translate – AI-based machine translation service

7.10.2024 by Jari Herrgård

Machine translation engines are a part of our everyday lives. We constantly use them in both professional and private contexts; however, we rarely put too much thought into how the translation itself is produced.

Machine translation engines help us in our daily work. They help us understand the texts we read, whether those texts are tendering information or the website of a local competitor, and also to produce text in a foreign language.

I would like to add a small note here: you should always have translations for published texts looked at by a professional translator, but an automated translation may be sufficient for email or chat use, for example.

LanguageWire Translate (or simply LWT) is our vision of what kinds of requirements a machine translation system for corporate use should meet. On the surface, it’s pretty similar to many of its competitors, but what’s inside is what separates it from the rest.

The key features of LanguageWire Translate include a deep-learning neural network translation engine, extremely strong security and utilisation of the customer organisation’s language resources.

Neural network translation engine

Deep-learning neural network translation engine technology has been tested time and time again in professional use and proven to be fast and reliable, with good-quality end products. When a sentence is longer than a couple of sentences, the engine can take the document as a whole into account instead of translating isolated sentences one at a time. This means the cohesion within the text can be better preserved and the context is better taken into account.

At the heart of LanguageWire Translate is the translation engine we developed ourselves, which has been trained on a large quantity of reliable language data.

The dawn of neural network translation was in 2017, and it remains the most efficient, cost-effective and reliable technology for professional applications. That being said, we naturally explore and already make use of large language models.

Would you like to hear more about our plans and current situation with regard to AI technology? Watch our webinar recording in which LanguageWire’s technical experts talk about our future plans and developmental leaps in AI translation.

Also read our article on large language models and the AI-based LanguageWire Generate content creation tool.

Information security

The level of security is what separates LanguageWire Translate from its free-to-use competitors. When you add text or files to the platform, you always know where your files go (the answer: nowhere). Also, LWT doesn’t store files for any longer than is required to carry out the translation assignment.

Thanks to these features, you can translate any content using LWT, and you don’t need to worry about the use of even confidential information. Right at this moment, it’s likely that you or your colleagues are using a free-to-use translation service to translate texts that could make your organisation’s information security officer raise their eyebrows. You can best prevent this by using a service in which even the most confidential materials are no problem.

The ISO 27001 certificate is just one example of why you can trust our machine translation platform. Naturally, the platform also meets the GDPR requirements.

Making use of your own language resources

Most organisations have some multilingual resources, and highly international and large companies may have lots of them. What lies behind the slightly obscure term language resources? The most important components are translation memories and glossaries, both of which can be fully used also in LanguageWire Translate.

Translation memories are translation databases in two or more languages that are always generated in connection with professional translation work. Glossaries are customer- or industry-specific termbases in at least two languages that are often used to facilitate the translation process.

When your organisation’s translation memory and glossary have been linked, they work seamlessly as part of the machine translation process. In practice, this means that if your organisation has previously had a phrase translated by us and that phrase pops up as part of a text that you have translated using LanguageWire Translate, you will get a reliable translation done and checked by a human. That’s also how the glossaries work.

You will also always see in the tool’s user interface which translations come from the translation memory or termbase and which are generated by AI, so that you will know which ones you need to check.

Ease of use

The translation of short pieces of text, which free-to-use services are known for, is also possible in LanguageWire Translate, and it is sufficient in many cases. However, if you need to have an entire document translated, copying and pasting text into the online user interface becomes cumbersome. Depending on the file format, it may even be impossible to copy all of the text at once and, at least by the time you’re reading the translation and possibly when moving the text back into the original file, things can get tricky. This is why LanguageWire Translate also supports the translation of entire files onto a web page by dragging and dropping.

The future of termbase management

18.4.2024 by Delingua

As we have seen recently, things can change very quickly in business technology. AI has leaped into our lives and is now becoming a major part of most of the daily processes and systems in ways we could never have imagined a year ago.

Termbases, critical business tools for those who seek quality and consistency in the content, and their related science of terminology management will be no different.

Peering into our crystal ball let’s see if we can catch a glimpse of a few of the future trends that will be impacting on our termbase management systems.

Cloud network storage

Long gone are the days when termbases were confined to a single desktop, accessible only by the one who created it. With cloud computing becoming much more ubiquitous in business, we can expect to see termbases becoming not just about storage but about accessibility, availability, and real-time updates. As businesses become increasingly global, the need for language experts to access these linguistic assets from anywhere, be it a bustling office in London or a quiet cafe in Kyoto, becomes imperative.

Cloud platforms don’t just facilitate this global reach; they also ensure that backup, security, and updates are managed centrally, reducing the nitty-gritty tasks for businesses, and freeing them to focus on their core operations. It also allows for greater levels of integration with more applications ensuring that you can apply your business language to your content, at anytime and anywhere.

Automation

Imagine a world where the process of updating a termbase doesn’t require manual intervention but is instead a seamless, automatic process. That’s where automation steps in.

Instead of combing vast amounts of content to identify and add new terms, automation tools, driven by AI, can detect, classify, and even suggest terms for inclusion. This not only streamlines the process saving you time and money, but also reduces the chances of error that manual processes can introduce therefore producing a much higher-quality final product.

AI data enhancement

Large Language Models thrive on data. The richer and more diverse the data, the more adept these models become by training the model with your specific business language. Termbases, teeming with linguistic intricacies, provide a golden opportunity here. By integrating termbases into AI training data, businesses can ensure that their AI tools are not just linguistically aware but are also culturally and contextually astute.

For businesses aiming for global resonance, this is a game-changer. A chatbot trained with a comprehensive termbase, for instance, would not just communicate; it would connect, understand nuances, and deliver a richer customer experience. Generative AI models would be able to produce content in your business voice using correct product names and ensuring consistency across the board.

Collaborative platforms

The beauty of collaboration is that it captures a myriad of perspectives. In the context of termbases, this means a more robust and diverse linguistic database. Collaborative platforms are set to revolutionise termbase management by enabling teams, irrespective of their geographical location, to contribute to, refine, and leverage a centralised termbase.

This collective approach ensures that the linguistic spectrum captured is broad, nuanced, and immensely valuable and specific to your business needs.

Looking forward in termbase management

The great news is that many of these exciting changes to greater improve and simplify termbase management are already here and improving day by day. You just need to understand and take advantage of them.

This article was originally published by LanguageWire Company (Verity Hartley)