How Artificial Intelligence is changing the entire Machine Translation Industry
Machine Translation is a subject that many people know exists but do not understand what it is about. Yes, we know it is an automated translation, but do you understand how it works?
Rodrigo Demetrio
2 min
Machine Translation is a subject that many people know exists but do not understand what it is about. Yes, we know it is an automated translation, but do you understand how it works? The term, used to designate texts translated by software, is mainly used in computational linguistics.
As an automated tool, Machine Translation has the potential to change the entire translation field. That is because, due to its technological nature, it can significantly reduce the costs of the translation of millions of documents. This will, in turn, help companies grow internationally, catalyzing globalization.To do so, scientists have already used many approaches, such as rule-based and statistical servers. However, the future points to a much faster - and more efficient- way to translate automatically: by using Artificial Intelligence. Here is all you need to know about the matter!
How Machine Translation began
Machine Translation, also known as MT, can be tracked down to 1629. This was the year that the French philosopher René Descartes started a conversation about a universal language. By using the principle of symbols and logic, Descartes proposed a new form of communication.
This universal language would be able to communicate equivalent ideas in different languages through one symbol. Originally, both Descartes and Gottfried Wilhelm Leibniz - a German mathematician - were thinking about numbers. However, as time passed, the concept of a universal language started to be applied to Machine Translation.
Since the 50s there has been much research conducted to translate mathematical texts into different languages. Eventually, this resulted in the modern form of Machine Translation. The 3 major approaches to Machine Translation are:
Rule-based machine translation (1950 - 1980)
Statistical Machine Translation (1990 - 2015)
Neural Machine Translation (2015 - Present)
Rule-based Machine Translation
Rule-based MT first started being developed in the 70s. This approach is also known as the “Classical Approach” of MT and relies highly on linguistic rules. As such, it uses a plethora of bilingual dictionaries for each language pair. Rule-based Machine Translation focuses on mapping out the rules in different languages.
Statistical-based Machine Translation
Statistical-based MT started being studied almost a decade after Rule-based MT and is based on statistical models’ parameters. These are developed through the analysis of a set of bilingual texts. Unlike Rule-based servers, Statistical based MT aims to create a pattern recognition and requires. Therefore, it requires a huge linguistic corpus to operate as intended.
Neural Machine
Neural Machine Translation (NMT) uses AI and deep learning to achieve more precise translations. Artificial neural networks learn to recognize patterns by processing large amounts of data.
These networks are learning algorithms that apply a nonlinear function to a group of inputs forming a layer. The operation generates outputs that will serve as resources for the next layer. There are multiple layers involved in the neural network, connected with weights/parameters. All of these layers get input with nonlinear features that increase possible combinations.
Hence, the encoder neural network processes a sentence in the source language and turns it into vector representations to be used in the decoder neural network, to predict the sentence in the target language.The NMT can learn from multiple sources of data and adapt to different contexts, as the model is easy to adjust and update with any desired database.
The training phase takes a few weeks, but the system can automatically correct its parameters. Once the output is generated and compared to the expected reference, you can send feedback to the machine and it will adjust the weight on the layers and the connections.
Statistical versus Neural Machine
One needs existing translations to feed the Statistical Machine Translation system so it can generate the hypothesis.As you gather bilingual texts corpora to work as input, the SMT results might vary according to the quality of these previous translations.
In the case of a less common language, it might be difficult to provide enough bilingual material to obtain good translations.Idioms, new slang and expressions, neologisms, language-play, and other components of literary and creative texts can also be a problem for SMT if these language uses aren’t present in the corpora used to train the system.
When word order from a source language is very different from the target language, results can also be less precise.Another disadvantage is that, once the system is implemented, it’s harder to fix bugs, as you need to restart it and check for other minor mistakes in data introduction.
source: SyncedReview
MT powered by Artificial Intelligence
Although the Rule-based, Statistical, and Neural approaches have their pros and cons, it is undeniable that they paved the way for what’s coming next in terms of Machine Translation.
If you do not know what we are talking about, here is a tip: it is heavily related to technology. The next generation of MT will rely on Artificial Intelligence and deep learning. And this is great news! AI and deep learning have the potential to transform MT and take it to a whole new level, as it will be able to make contextualized decisions in regards to the meaning of words and terms. AI will also make it possible for MT to better recognize patterns between a language pair. The entire translation process will not depend on translators alone - they will switch roles, becoming reviewers and testers of the output.
This will result in faster, cheaper translated documents, which will ultimately deliver better results and facilitate the communication between people who speak different languages. We could optimize the rate of words translated by 3,4, or 5 times than before - the sky's the limit! In this sense, it is also important to learn new ways in which we can measure the quality of the content translated.
One of the best ways to do so is by using the BLEU score, an algorithm capable of measuring the quality of automated translated texts. MT driven by AI and deep learning will make it possible for thousands of businesses to contemplate going global. It will also help international organizations to stay in the market and even enter others. As the cost will be significantly lower, companies will not have to make cost-based decisions when talking about what languages to prioritize.
Companies will be available anywhere in a localized manner. It seems great, right? And it is! Still, it is important to notice that we are talking about the future. We have a long way until we get to the point where we can relate solely to AI to translate. As with any other incipient approach, it will likely take a few years to fully develop this new technology - and some more to completely absorb the technique.
The Translator’s Future
Of course, there are also a few challenges along the way. The role of a translator, for instance, will have to be almost completely redefined to not become obsolete. However, this also represents a great chance for these professionals to reinvent themselves.
We have to look at this as a challenge to overcome - not as a problem. That way, we will be able to enjoy the positive aspects that Artificial Intelligence and deep learning can bring to Machine Translation. By being open to novelty, learning, and adapting, we can turn MT into a deep social and economic transformation and re-emerge on the other side as more aware and better-equipped people able to conquer the challenges that we face.
Collaborative translation is a powerful tool for your business if you’re looking to expand to new global markets. By coordinating a team of professionals who work together in real-time, you can quickly deliver high quality translations that resonate with local audiences.
But what if you don't know how to synchronize a large team's efforts? Or are you struggling to find the right software for a well-coordinated translation process? Well, look no further! In this guide, you'll learn all the know-how's of collaborative translation to bring your brand to global audiences.
Overview
What is collaborative translation?
Why seamless translation collaboration is important
Best practices for collaborative translation and global market success
What is collaborative translation?
Collaborative translation is when multiple people simultaneously work together to translate content. A collaborative translation process often makes use of specialized tools and software to make sure the translation is quick, accurate, and consistent.
Example: Let's say you're a B2B SaaS company looking to translate your marketing materials into a new language to connect with potential clients abroad. Use collaborative translation to bring together translators, developers, and other specialists to translate content into many languages at once.
Your team can use a collaborative translation platform like Redokun to work on projects simultaneously. A coordinated workflow will make sure that your translations use the same terminology and style, improving the quality of the translated product for your target audiences.
Collaborative Translation vs. Crowdsourcing
People often confuse collaborative translation with crowdsourcing and think the two are the same. However, these approaches to translation are different.
Crowdsourcing is when a large group of people contributes translations, often through an open call or invitation by a company or author. Brands can turn to crowdsourcing, community translation, or volunteer translation when they are looking to reduce costs and accelerate the process, especially for large multi-language projects.
In crowdsourced translations, the contributors can be volunteer translators, subject matter experts, or just anonymous individuals online. In other words, you may not know who's worked on the translation and what their qualifications are. It makes crowdsourcing distinct from collaborative translation, where the team would be an established group of professionals you've selected
Why seamless translation collaboration is important
As a busy B2B/B2C marketing manager or project manager, you might ask yourself: Isn't the "divide and conquer" a better strategy when working on a translation or localization project? It seems logical that each project team member, including translators, designers, and editors, works on their tasks separately and step by step.
However, collaborative translation can help your team reap many benefits compared to a traditional approach to translation projects:
Produce high-quality translations consistently. When your whole team works on a translation project simultaneously on one platform, it's easier to stay in context and keep track of the translation accuracy for every target language. On top of that, your team can conduct agile QA throughout the project cycle.
Faster turnaround times. By working together, your team can complete projects faster and more efficiently. Centralization saves a lot of time at every stage of translation. And since your team can work on more than one translation at a time, you can publish your translated content in several new markets at once.
Reduced costs. You get to improve efficiency while working with a smaller team of translators. The smaller and more coordinated the team, the less the risk of costly translation errors. It means reduced translation costs and better project budget compliance.
Increased flexibility. Collaborative translation allows your team to produce translations into many languages at once and easily make changes to any project document. You can conveniently engage in a feedback loop and guarantee a continuous localization process.
Better communication. Collaborative translation effectively brings all members of your localization team together on one platform. It helps you make sure that everyone is working toward the same goals and simplifies overall localization management.
Six best practices for collaborative translation and global market success
To be great at collaborative translation, you need to approach it strategically. Even if you've never used this approach before, you can follow the six steps below to build an efficient collaborative translation workflow. And if you're already familiar with this method, these practices will help you improve the way you collaborate on any translation projects.
1. Work out a detailed project plan
Before you start working on translations together, you need a clear-cut project plan. You should first identify the following items.
Project timeline: Define crucial deadlines, project milestones, and the overall project duration.
Translation volume and key deliverables: Calculate the general word count, and determine the workload for every language pair if you translate into multiple languages.
Project team: Define what kind of specialists you need: translators, editors, proofreaders, etc. Will you need to find external translators? Consider all your HR needs in advance.
Your approach to the translation process: How much do you want to rely on machine translation? At what point will you edit translated strings? Answer all these questions before you go on.
Quality assurance protocol: Establish an efficient QA procedure for all the language pairs you're working on.
It may sound like a handful but the more detailed the plan, the more streamlined the translations will be down the road. Besides, you can already use Redokun to boost this stage of the localization process!
Redokun is a translation management system you can use to automate, coordinate, and optimize your translation processes from content creation to publication.
Redokun simplifies your project planning. In particular, you can use the tool to:
Monitor your ongoing translations easily. Keep track of all of your translation files and projects across multiple languages in one space, and check their progress at a glance.
Meet deadlines with digest emails. Redokun will send you daily or weekly email digests to update you on the progress of translations. From there, you can initiate one-click reminders to your translators who are potentially falling behind schedule.
Making budget planning easier. Redokun has a transparent, scalable pricing structure that will cover exactly the volume of work your project needs.
Redokun is an easy-to-use tool that requires no onboarding. Your team can start using all the system’s features right away. During your project planning stage, you won’t need to factor in a lengthy training period to introduce team members to the tool.
2. Divide tasks and assign responsibilities the smart way
Good collaboration is impossible without a well-planned distribution and organization of roles and tasks. Ensure that every team member is on the same page and understands their respective responsibilities.
For example, the project managers should divide translation tasks among translation team members according to their language proficiency, area of expertise, or subject matter knowledge.
On Redokun, you can invite translators to work on different language pairsand content types depending on their skills. All you need to do is enter the translator's email. The software will send them an email invitation and let you know once they've started translating the file.
You can also invite several translators to work on one document.
To maximize the efficiency of project management and task division, establish a clear structure of your workflow. Make sure all your pages, files, and folders are well organized and team members know where to find necessary resources for their respective tasks. A centralized, cloud-based storage for all your documents is a must.
Redokun is a cloud-based software that makes file management easy. You can create folders and customize permission settings for multiple users for better organization. No more need to look for spreadsheets and lost documents scattered around different digital locations.
Don't forget to make the most of the Reporting Dashboard. It shows you the status of the translation project and helps you see how users distribute tasks (for example, what methods they use to translate different content segments).
3. Enhance the collaborative translation process with clear communication
It's important to have open communication channels among all team members in your translation project, including internal and external translators. For a successful collaboration effort, you need a shared communication space to:
Conduct regular check-ins.
Discuss translation options and other aspects of the working process.
Update and adjust requirements and guidelines.
Maintain feedback loops.
It's up to you to choose between email, messengers, or tools like Google Drive or Slack to keep your collboarative operations flowing. However, using multiple channels for different aspects of the project can get messy. It's harder to manage your team and make sure all collaborators are up to date on the ongoing translation tasks.
You can avoid these potential problems by centralizing all your communications and project management. With translation software like Redokun, you can manage, translate, communicate, and collaborate — all in one place.
Translate content in context. Your translators or editors can use page previews in Web Editor to understand the context of the text while working on it.
Work together in real-time. Use Redokun as a full-scale collaborative translation platform. It enables real-time cooperation among your team members, improving efficiency and reducing communication errors.
Use comments, mentions, and notifications to exchange feedback quickly. Redokun's Web Editor is a convenient place to stay in touch and discuss your translation progress every step of the way.
Create a hybrid workflow. Work with your in-house teams or external translators to suit different localization project formats and scalability needs.
4. Use machine translation and translation memory tools
Computer-assisted translation tools are a great addition to human translation. Machine translation (MT) helps your collaborators speed up the localization process by automating translation. Of course, it doesn't have the quality of a human professional translation — it’s more like a helping hand that's always there to facilitate the translation of complex phrases or new terms.
Redokun is integrated with two Machine Translation tools: Google Translate and DeepL. Translation suggestions by these two tools pop up right below where the translator should key in the translation, as shown here.
To enhance collaboration even further, consider using translation memory tools. They ensure consistency and save translation software users a lot of time.
Translation memory (TM) is a translation technology that stores previously translated sentences or phrases as segments and creates a unique database for your localization projects. You can reuse your translation to increase efficiency and consistency in ongoing and future translations.
With Redokun as your collaborative translation platform, you can leverage TM to:
Consistently translate any repeated word, phrase, or sentence across different language pairs and documents. It's especially important for translating technical terms, marketing slogans, CTAs, and other catchphrases. Translation memory helps you stay consistent in your marketing messaging.
Pre-translate your entire documents. Combine TM matches from your previous translations with Machine Translation to get a fully pre-translated document even before your team gets to work.
Manage your translation memory database. Import and customize your TM database to further improve translation quality and consistency.
”The speed of translation is quite impressive in that it doesn’t take [much time], maybe a couple of minutes when you translate from English to eight markets. I think that’s what I’m most impressed by.”
Read more about how Kenni and the marketing team at Rockfon increased their translation productivity by 70% using translation memories and other Redokun features here.
5. Use glossaries and style guides
Glossaries and style guides are valuable resources your team can use for reliable reference.
A glossary is a list of terms and their corresponding translations that are specific to a company or industry.
A style guide outlines the preferred tone, voice, and style for a company's marketing materials across markets and languages.
Your collaborators can refer to these resources when they’re not sure about a translation. For example is when they're deciding how to translate a company abbreviation, whether to the Oxford comma, or choosing the right tone to address customers, etc. No more ambiguity about linguistic, stylistic, and cultural aspects of your translations.
Use Redokun's glossary feature to create a glossary and style guide that outlines rules for spelling, grammar, punctuation, terminology, and tone specific to your project.
6. Continuously review and revise
A key benefit of a collaborative translation platform is the ability to review and revise translations in an agile and efficient manner. By involving multiple specialists in the process of editing and QA, you can guarantee accuracy and consistency in the translated content at every stage of the project.
To implement effective review and revision procedures in your collaborative translation projects, it is important to:
Plan for review and revision in advance. Identify who will be responsible, set the timeline, and use specific tools.
Consider involving in-country reviewers who are familiar with the local market and culture to ensure that the translations are accurate and appropriate for the target audience.
Perform regular QA checks. They should include consistency in terminology and formatting, and verify that the translations are free from grammatical errors and typos.
Pro-tip: Ever experienced the headache of having to update a translation that’s already 70% done when there is a last-minute change to the source document?
With Redokun’s revision feature, you don’t have to spend hours poring over Excel sheets and comparing files to spot the places where new words have been added or sentences have been changed. Just upload the latest document version and the system will identify new text that needs translating — saving your team’s time and effort while keeping previous translations intact.
Summary
Collaborative translation is an excellent approach if you want to improve the consistency of your translations, reduce costs, and establish a strong presence in global markets.
The key to seamless collaboration is a combination of careful planning, role distribution, agile QA, and smart use of translation software.
Make Redokun part of your collaborative translation efforts and enhance the pace of your global business growth. Start your 14-day free trial today and benefit from a quicker and more streamlined translation workflow.
Till next time,
Anastasia
Rodrigo Demetrio
Steering the marketing ship at Bureau Works with 17+ years of MarTech under my belt, I transform mere ideas into tangible realities. Passionate about languages and their power to build bridges, let's build a new one?