Maschinelle Übersetzung Leistung

Machine translation

Translation agency with AI experience

This page has been machine translated and post-edited. This page is an example of what machine translation and post-editing are capable of.

Automatic translation of your texts

D.O.G. MT Solutions

In today’s world, cost-cutting measures are at the top of many managers’ priority lists. The interest in machine translation(MT) is greater than ever.

“How much can I save with machine translation?”
“What is the quality of MT and for which texts can I use it?”

These are some of the questions on the minds of many today. Here, we provide you with concrete answers and decision-making guidance. You can also download our whitepaper, which explains in detail how MT works and the usage scenarios.

Whether you are just looking for information, want to test MT or train an engine, contact us. We will be happy to help and advise you!

Machine translations have long been ridiculed. Since the successes of Google Translate and DeepL a few years ago, they are considered an important technology for the production of automatic translations. Expectations are high: reduction of translation costs with equivalent quality thanks to post-editing by trained post-editors. Is this possible? Yes, but not for all documentation and not for all goals.

D.O.G. began to actively address the topic of “machine translation” back in 2008. At that time, it was a joint research project with the French university ISIT: “Enhancing Machine Translation Quality with ErrorSpy”. This project resulted in functions in our ErrorSpy quality assurance software that can be used to better detect and correct translation machine errors.

certified
Machine translation into all languages
We translate into all languages

Do you need an automatic translation? We will send you a quote within the shortest possible time. Send us your request using this quote form.

Click or drag files to this area to upload. You can upload up to 10 files.
For larger volumes: use our transfer drive

All-round solution for machine translation

What MT solutions does D.O.G. offer you?

Training progress: evaluation score

Training progress: gradient

Download MT whitepaper

Download our whitepaper! (In German)

Challenges of machine translation

We have the necessary knowledge

Machine translation yes, but not for all texts

Companies produce and use a whole lot of information. They serve different purposes (pure information and communication, advertising, operation of machines, etc.), are legally binding or not (like the instruction manuals specified by the European Machinery Directive 2006/42/EC), are formulated in a sophisticated way or are highly standardized.

Depending on how these characteristics and criteria turn out, machine translation is recommended or not.

In general, it is important to know that machine translation works better when:

MT is not necessarily a competitor to translation memory systems. It is rather another tool with which translations can be produced.

Machines make other types of mistake

People make mistakes, machines do too, but others. For example, they translate proper names, do not understand many abbreviations, or add information that does not appear in the source text. They also sometimes omit words during translation. This is not always easy to detect, especially if the translated sentence otherwise sounds good.

That is why it is important to train post-editors, to inform them about the types of errors they need to look for. And the typology of these errors differs depending on the type of translation engine used: statistical machine translation (SMT) systems make different errors than neural machine translation (NMT) systems.

Since its foundation more than 20 years ago, D.O.G. has been working very intensively on the topic of translation quality and, since 2008, specifically on the quality of machine translation systems. We have developed our own tools and metrics to check this quality. Before machine translation starts, we identify the segments that are not suitable for the MT process and sort them out or mark them for further processing steps.

You can benefit from our experience.

Costs and benefits

Implementing a machine translation solution for your company is a project with two main components: setting up the system and getting value from the system.

Setting up a machine translation system: a model must be trained for each language combination. To do this, the system needs relatively large amounts of high-quality bilingual data. Training is done on special computers with GPU (Graphics Processor Unit) that allow massive parallel processing. Training can take several machine days and the training parameters must be optimized in several test runs. This is a cost factor.

Operating and using the system: Even in the deployment phase, the system must learn from errors and be trained with new topics and data. Finally, there is the cost of post-editing, which basically reflects the time that post-editors invest in correcting machine errors.
We charge separately for setting up the solution (a one-time cost) and for using the system. Thus, for the ongoing operation you pay a price per word that is lower than the cost of a human translation. After agreeing on the key data for your solution, we can provide you with a quote for this.

The cost-effectiveness of an MT solution ultimately depends on its deployment model. If you are already making big savings by using translation memory systems and want to machine translate the same documents in the future, then the savings might be rather small. However, if you are translating new texts and content that you have not translated before or have translated without translation technologies, then the profitability of a machine translation solution increases very quickly.

Your automatic translation in 9 steps
Workflow to your MT solution

Do you want to set up a translation portal
on your intranet that delivers fully automated translations? Do you want to support translators during their work with CAT tools (Computer-Aided-Translation Systems = Translation Memory Systems)? Or do you need post-edited documents that have a similar quality as human translations?

What do you want to achieve?

Set goals and expectations.
In a working meeting, we go through your situation and weigh up the various options. This results in concrete goals and work steps.

How do you plan to achieve it?

Determine translation engine and the infrastructure.
From the different options for machine translation production, we choose the variant(s) that is most suitable: training a D.O.G. MT engine, training via an MT platform or using a standard engine such as DeepL.

Training data for different languages

Collect training data.
Depending on the languages and content required, we collect appropriate training data.

Linguistic data optimization

Clean up training data
The quality of the translation results strongly depends on the quality and nature of the training data.

Structure of the base engine

Train the engine.
We train engines for the desired language combinations and subject areas. These engines are re-trained at regular intervals with new material and insights from post-editing.

Use of the engines

Translate with the engine.
The first translations are created automatically and forwarded to the post editors.

Quality assurance of translations

Post-edit the result.
Experienced post editors, working according to DIN ISO 18587, search and correct MT errors.

Learning from the MT errors

Evaluate feedback from post editors.
We evaluate the post editors' reports to optimize terminology and retrain the engines.

Engines update

Optimize the engine (ongoing).
The engines are updated periodically to reflect new issues and the results of post-editing.

Depending on the objective, different workflows and implementations are considered. Here, too, our team of specialists and software developers will help you implement the right solution.

Language combinations

Automatic translation with post-editing in these languages

We offer a wide range of language pairs for machine translation. Here are some of the most requested language pairs:

Machine translation + quality

Quality and time saving

Maschinelle Übersetzung – die Daten und das Training

The data and the training

Good data is crucial for machine learning. According to the motto “garbage in, garbage out”, the success of machine translation strongly depends on how extensive and how clean the training data is. First and foremost, translation memories (TMs) are the most suitable for training. But due to their creation history, TMs contain many segments that interfere with training: Empty segments, incorrectly assigned translations (e.g., in the case of incorrectly segmented sentences), or inconsistent terms and phrases.

Training is not a one-time affair. New texts and topics are added. Machine errors can be corrected through post-training. Our post editors give us regular feedback on typical recurring machine errors. Our developers use this information to retrain the translation engines on a regular basis. In this way, the engine adapts better and better to your linguistic wishes and specificities over time.

You can also benefit from our experience here. We help you optimize the training data to achieve a better result. We have developed methods and tools for this.

Machine translation and data security

An important reason for many companies to opt for machine translation is data security. No company management wants to be responsible for confidential information being tapped inadvertently because careless employees have it translated via a free translation service on the Internet.

The engines we train for you are either located on our own server in Germany, which is operated in accordance with EU law (GDPR, General Data Protection Regulation), or via secure cloud services in Germany.

You also have the option of installing the trained engine on your own server.

Maschinelle Übersetzung und Datensicherheit
Post editing Maschinelle Übersetzung

Post-editing according to ISO 18587

Many companies require machine translation solutions in conjunction with post-editing. Although the new standard on the post-editing of machine-produced translations (ISO 18587:2017) defines two post-editing levels Full and Light Post-Editing, in practice the criteria for acceptable quality depend heavily on the objectives pursued and engines used.

We help you to define the optimal quality targets for the work of post-editors for the solution you have chosen. This leads to specific guidelines for the work of the post editors.

Welches Engine bei maschineller Übersetzung
Translation systems
Which engine?

If you want to travel to Rome, then you can choose between different means of transport. The same is true for machine translation. There is not one system and approach, but several alternatives depending on your objective, data volume and budget.

Thus, you can definitely choose between alternatives such as the following:

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FAQ
These questions are often asked in connection with MT

Yes. The risk of serious errors is greater with machine translation than with human translation. Some sentences read very well. However, some important information is missing or a statement has been misunderstood. This is not always recognized by inexperienced post-editors or post-editors who do not know the subject. With trained post-editors and quality assurance tools, as well as terminology optimized for MT, this risk can be significantly reduced. However, it can never be completely eliminated. A decision in favor of MT must therefore also take these aspects into account.

The cost of training an engine is not small. First of all, the hardware or infrastructure. Because of the very large amounts of data, you need powerful computers with very large memory. One can buy these computers or rent the infrastructure. Then, collecting and cleaning the training data costs time and money. Finally, the training itself, which requires a lot of know-how and some trial and error until the optimal engine configuration is found. Therefore, training a single engine (per language pair) is only worthwhile if the corresponding volumes of texts to be translated are available. Furthermore, in many cases the additional advantage of MT must be weighed against the existing advantages of translation memory systems.

The DIN ISO 18587 standard deals with post-editing and specifies the requirements for the qualification of post-editors. From a pragmatic point of view, post-editing is different from the revision of human translations, even though there are many similarities. The post-editor must be able to suppress the desire for perfection and limit himself to the necessary corrections, depending on the requirement for the quality level of the final result (full post-editing or light post-editing). He needs to know what specific types of mistakes MT machines make, because machines sometimes make mistakes that never or very rarely happen to humans (e.g., adding text). That's why it is important to use service providers like D.O.G. GmbH who have experience with post-editing.

Technologies for successful machine translation

Technologies from D.O.G. to your advantage

The success of machine translation solutions stands and falls with the ability to detect translation errors and use the correct specialist terminology. This is where D.O.G. has very special technological advantages. Since the company was founded over 20 years ago, we have made it a priority to develop software products that support the quality of our translations. In particular, ErrorSpy and LookUp help us do just that.

LookUpis an intelligent terminology management system. In LookUp, relations between terms can be recorded, making contextual information available. Our software-based checks take these relations and your terminology into account. As a result, our post-editors are better able to detect machine errors.

ErrorSpyhelps post editors detect and correct machine translation errors:

The AI know-how of D.O.G. developers and the ability to directly influence machine translation systems bring significant benefits already. You can benefit from this.

German Human DOG Engine DeepL Kommentar
Status Fehlteil setzen
Set status reject part
Set status reject par
Set missing part status
Terminologie wurde gelernt (Kein Sinnfehler)
Das Handling wurde von der Maschine angefordert.
Handling was requested by the machine.
Handling was requested by the machine.
The handling was requested by the machine.
Stil wurde gelernt
Cause:
Cause:
Cause:
cause:
Groß-/Kleinschreibung wurde gelernt
Als erstes muß die Datei Einstellungen.cfg vom Hauptverzeichnis kopiert werden.
File Einstellungen.cfg•must be copied beforehand from the main directory.
First copy the file Einstellungen.cfg from the main directory.
First, the Settings.cfg file must be copied from the root directory.
Dateinamen (named entities) und Terminologie wurden gelernt

Translation service

Automatic translation of your texts

These are some of the texts we machine translate. Of course, we also offer human translations.

Are you interested in machine translation?

Why not get in touch with us? In a non-binding conversation, we will discuss how MT can help you achieve your goals.

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