Archives for March 2024

Validation – high-quality translations are a joint effort

27.3.2024 by Jari Herrgård

Successful translations require teamwork. Although the key person in the translation process is the translator and their tools, they alone are not able to achieve ideal quality. In the translation process, the best possible result always requires input from the translation agency’s other employees as well as the customer. Validation is perhaps the most important tool for assessing the linguistic quality of translations.

If you are a customer, you may be asking why you should contribute to the process – it’s our job, after all. You are correct and, as a customer, your involvement is not obligatory. But if you want the best result, it is in your best interest to participate in the process – especially through feedback.

To some extent, language is a matter of opinion. We are all fluent in at least our own native tongue, and many of us also know several other languages. Therefore, we all have a lot of opinions about language. This is especially true in work contexts if language plays a central role in our work and we put a lot of thought into how a message should be conveyed. We know how we want to address the reader, and perhaps the organisation we work in has even defined common rules for what kinds of images we should evoke.

Even if these rules are self-explanatory within the organisation and come naturally to you, they may not be self-evident to the translator. The translator is always a bit of an outsider and depends on what they are told about your preferred language and its nuances. This is where teamwork comes into play: the ideal translation process involves cooperation to ensure that the translation matches the customer’s communication needs as closely as possible. By providing feedback on the translations, the customer can ensure that each translation is better than the one before and closer to the customer’s ideal.

Validation as a tool

One of the most important tools for the process described above is validation. This means a review by the customer after the translation has been completed. It may often be carried out by an expert whose main work tasks do not include translation. The expert is responsible for checking, in particular, the terminology and style, and assessing whether they are in line with the customer’s brand. Other review work can also be done at the same time.

Validation in itself is a simple step, and there is no doubt about its usefulness, but it is still often skipped altogether. Typically, validation is carried out by sending PDF or DOCX files to vendors or technical experts, for example. The expert will use the comment or track changes functions to add their own comments and corrections to the document. These will be included in the final version and imported into the translation memory by the translation agency. This process is quite laborious and may complicate version control, which are the main reasons why it is often skipped.

Validation with system support

At LanguageWire, workflow and translation work are based on a shared platform used by customers, translators and internal project managers. Using a single platform has many benefits, especially in terms of translation project communications and transparency.

The validation step also takes place entirely on this platform, which makes the process quick and efficient. Usually, the validation step is added as soon as the project is created.

Validation takes place after the translators have done their work. The experts assigned to the project will receive an automatic message from the system and, by clicking on the link, they will be forwarded to the right project. There is no need to search for the project or upload any files, and the expert can start working in their browser right away.

Validation is done in the same tool that the translators use, and the validator has access to all the same information. This means, for example, that they will automatically be able to view the correct terminology if there is a glossary attached. This helps to avoid situations where outdated or otherwise incorrect terminology is used in the text during the validation phase. The validator also has access to other tools, such as proofreading and translation tools. Our user-friendly interface ensures that you do not need to be a professional translator to benefit from the translation platform. Everything you need can be done with basic browser skills.

In addition to possible corrections, the validator can also communicate with the translator, which helps to quickly solve potential dilemmas. Since everyone works in the same digital environment, all corrections are also saved directly in the translation memory, and they do not need to be separately exported at the end of the project.

In order to ensure the best possible translation quality and that the translator and proofreader learn as much as possible, a language specialist will check the changes made by the validator at the end. This ensures that all changes follow the customer’s own standards and, of course, the general rules of the language.

Would you like to discuss your organisation’s language needs? Contact us via email at contact-fi@languagewire.com for further information!

Artificial intelligence – the latest localisation superpower

22.3.2024 by Delingua

Simultaneous interpreting – what is it?

21.3.2024 by Katja Virtanen

Have you ever tried listening to one language while at the same time saying the same things in another? That is, not only translating words one after another but paying close attention to all the nuances of the language and what the speaker really wants to say?

Even the smartest smart devices can’t do that, but professional simultaneous interpreters can.

What is simultaneous interpreting?

Interpreting in which the interpreter translates – or rather interprets – into another language at the same time as the speaker speaks is called simultaneous interpreting. It is exactly this idea of everything happening at the same time that sets simultaneous interpreting apart from other forms of interpreting in which the speaker and the interpreter take turns speaking.

Simultaneous interpreting is often called conference interpreting as it is typically used at conferences, seminars and different meetings. For example, an annual general meeting may be held in English, the company’s working language, but Finnish-speaking shareholders can listen to the meeting in Finnish in real time.

Since interpreting takes place simultaneously, simultaneous interpreting does not take up extra time and can “happen in the background” without disturbing those who don’t need it. At the meetings of international organisations, you might notice interpreting only from the fact that participants are wearing headphones, even though dozens of languages are being interpreted in the interpreting booths.

What happens in an interpreter’s brain?

Simultaneous interpreting is challenging both physically and cognitively. An interpreter listens to the speaker, processes what they hear, stores information and produces speech in another language simultaneously. Linguistic understanding alone is not enough: in addition, the interpreter needs an excellent ability to concentrate and to pick out the essential elements that make up the idea to be interpreted.

In addition, there might be other stress factors, such as poor sound quality, the speaker’s strong accent, speeches read quickly and directly from paper, unfamiliar terms and abbreviations, fatigue and stress. No wonder the work of a simultaneous interpreter is often compared to working as an aircraft pilot or a heart surgeon!

According to several studies, many cognitive systems are activated in the brain during simultaneous interpreting. These include at least listening and analysing, the working memory needed for remembering what has been heard and the ability to produce speech in the target language.

How does a simultaneous interpreter prepare for an assignment?

It is said that most of an interpreter’s working time is spent preparing for their next interpreting assignments. This may even go unnoticed as interpreting services are normally invoiced on the basis of the time spent on interpreting itself.

The interpreter prepares for each assignment separately, but they also prepare themselves on a general level by constantly accumulating general knowledge. Before an interpreting assignment, the interpreter goes over glossaries and texts related to the topic in question as well as any materials they receive from the customer. It is the customer’s task to enable the simultaneous interpreter to prepare for the assignment by delivering the meeting materials in advance.

Remote simultaneous interpreting

Before the coronavirus pandemic, simultaneous interpreting was mainly available at meetings where both participants and interpreters were present at the meeting venue. However, in these exceptional circumstances, the need for remote simultaneous interpreting increased exponentially, and today more and more meetings and conferences offer the opportunity of remote participation and also remote simultaneous interpreting.

It is possible to incorporate interpreting in, for example, the most common videoconferencing services such as Teams, Zoom, GoToMeeting, etc. In addition to this, there are hybrid models where the conference or meeting is organised on-site to some extent and only participants attend remotely. In practice, participants can, in both cases, listen to one of the language channels offered either with their computer or smart device.

Why should you offer simultaneous interpreting?

It should be kept in mind that even if people have small talk skills in a language, their language skills may not be sufficient to understand special terminology or complex linguistic structures. Speeches and presentations may be superficially understood, but the nuances of the language, the deep meaning of the message or the quick speech of a native speaker, for example, might not be fully understood.

When participants have the opportunity to follow the meeting or the conference in their own language, they get the feeling that they and their language needs have been taken into account. By offering simultaneous interpreting to a participant with insufficient or no skills in the speaker’s language, the organiser responds to the needs of customers or participants, which is one of the key issues, especially in the world of business.

Large language models – what are they?

13.3.2024 by Sohvi Kähärä

Over the past year, it has been difficult not to come across content created by generative AI.You may have seen a LinkedIn post where OpenAI’s AI-based ChatGPT has been asked to give good tips on how to get a salary raise. Perhaps you have encountered a chatbot when you have needed help with booking an appointment online. You may have even laughed at images created by DALL·E, where the faces of familiar celebrities have been digitally added to classic works of art.

Generative AI is developing at a tremendous pace and language technology is also benefiting from these leaps of development. From the perspective of language technology, the most important role is played by large language models (LLMs).

Large language models need massive amounts of data

Generative AI solutions created for producing and processing language are called large language models. They are statistical models that calculate the probabilities of the occurrence of words or parts of words. The simplest language models calculate the probability simply by calculating how many times the word appears in the given text materials, without taking the surrounding words and their meanings into account.

Large language models, on the other hand, are advanced language models that are based on neural networks and, as their name suggests, are trained with large amounts of data. The training of the language models of previous neural machine translation engines often requires a dataset of hundreds of millions of variables but large language models require billions of them.

Current neural network-based language models, including large language models, are most often based on transformers. Transformers are neural network architectures that consist of many overlapping layers. Previous machine learning models focused on individual words in their training data, while transformers are capable of simultaneously processing and taking into account words within a sentence or a longer text and analysing, among other things, broader relationships within the sentence.

Large language models use huge text materials to learn which words appear in which context and which words often follow each other. This allows large language models to predict what words and phrases would appear in an answer suitable to a certain type of question, how a beginning of a poem could continue or how a certain matter would be expressed in another language in the context in question.

A one-size-fits-all solution is not suitable for all cases

Since the amount of data needed for training large language models is enormous, a lot of generic content will inevitably have to be used. Large language models can also be customised, or personalised, to make them more suitable for different tasks and needs. This can be done by adding additional training data in a more limited subject area and modifying the model’s weightings. It is also important to choose a suitable customisation strategy, such as building a ready-to-use model or learning through use with the aid of prompt engineering.

Especially when large language models are used for translation, it is useful to personalise language model with high-quality, fully matching bilingual materials. It is especially good if the texts used in personalisation and the new texts to be translated are from as similar subject areas as possible. For this purpose, training language models with existing translation memories is a good idea: all of the customer’s translations are saved in translation memories by language pair so these texts are always bilingual, are good matches and use the company’s desired style and terminology.

In this way, the language model learns what the customer’s texts are like and is able to imitate their style better in the future. This improves, among other things, how machine translation produced by large language models is aligned with the company’s style. This, in turn, speeds up translating as higher-quality machine translation that is customised according to the customer’s needs reduces the time involved in any post-editing required.

The downsides of AI

Although continuous learning and adaptability associated with large language models are in many respects good, they also have their downsides. Language model-based solutions in general use learn as they are running so they can also be intentionally misled and taught false information. If you repeatedly teach a language model that a pike is a bird instead of a fish, it will start believing this to be true. Large language models also suffer from so-called hallucinations, which you can read more about in our article on getting the most out of machine translation.

In addition to invented facts, another risk associated with language models trained with a large amount of data is that confidential information ends up in the wrong place. Large language models in general use are open to everyone and, when using them, it is not possible to be sure whether your data will be made available to others. Therefore, it is important to choose a reliable partner for whom data security issues are a priority.

When training large language models with translation memories, it is necessary to take care of data security and ensure that customer-specific data is used only in each customer’s own model. This way, you can avoid the situation in which the language model would introduce another customer’s confidential information into the translation. We can build a customer-specific language model directly as part of LanguageWire’s highly secure ecosystem. Read more about LanguageWire’s insights into the data security in large language models here.

Large language models as part of the future

Training large language models for translation needs is a giant leap forward as they can provide more accurate and natural translations into multiple languages. These models make it possible to produce translations quickly while taking into account the desired style and terminology. In the future, this development can break down language barriers and foster interaction between people around the world by strengthening understanding and cooperation on a global scale.

5 reasons why integration is a good idea

5.3.2024 by Delingua

LanguageWire’s APIs and connectors are a time- and effort-saving solution, helping you avoid copying text unnecessarily from one place to another and import any changes, no matter how big or small, to all language versions of your website in almost real time.

A connector is a kind of system integration that allows the customer to order a translation of the content through an existing publishing system. In practice, a customer who uses a publishing system to process their website content can use our connector to order website translations from within their content management system. Once the translations are ready, they are imported into the system as localised copies of the original page.

We have listed five key reasons why integration is a good idea.

1. Work in a familiar publishing system

LanguageWire connectors and custom API work with your CMS, PIM or DAM. You can order translations and track the progress of projects directly through the digital platform you are already using.

Integration can be built with nearly any generally used content management system. We have Adobe, Drupal, inRiver, Optimizely, Sitecore, TYPO3, Shopify, Umbraco and WordPress connectors – and many others! If you didn’t find an option suitable for your platform among our connectors, you can use our API to create a custom integration between your digital platform and LanguageWire.

2. Automate your translation management process

Copying source texts from websites and emailing them to be translated is a time-consuming process. A smarter and more efficient way to manage large volumes of website content and numerous language versions is to integrate the systems so that the process for managing the translations is as highly automated as possible. Managing online store product information in different language versions, for instance, is much easier when the processed are automated.

LanguageWire’s APIs and connectors make full automation of the process possible. Simply connect your application to a tech-enabled translation management tool, and your translations can be imported directly from the translator to the page.

3. Save time and reduce workload

By using integration, you can publish content in every language as simply as in one. Integration is a better option than time-consuming manual work, and you receive ready translations right into your own publishing system. Managing translation orders is quick and easy with a user-friendly interface. This allows you to save time and money and, above all, gain additional peace of mind when the most monotonous part in the language version release process can be eliminated. With aid of a connector, you can import any changes, no matter how big or small, to all language versions of your website or webstore in almost real time.

4. Minimise risks

Furthermore, the likelihood of making mistakes increases when a large number of files are sent back and forth, with internal editors’ modification proposals. With LanguageWire, you don’t need to make any compromises on security. HTTPS-encrypted transfer of data increases security and you can manage the integration between LanguageWire and your system with modern access control.

Our APIs are built to be very stable so you don’t lose any jobs or complete translations in the event of a network outage. With integration, you can send texts for translation securely without a flood of emails and a need to worry about human errors.

5. Higher translation quality

We work as an extension of your business by building a permanent team of project managers, linguists and engineers. By connecting your digital platform to LanguageWire’s system, you will have access to our network of over 7,000 language experts. Our experts translate more than 450 million words per year, in 500 different language pairs. No matter what languages you are looking for or what sector you work in, we’ll bring you in touch with a language expert who best meets your company’s needs.

Interested? Contact us – let’s make translation management easier!