“Translation Check” – The AI tool for checking document translations

Fast and error-free processing of annual reports: "Translation Check" enables controlling departments and agencies to check and adapt annual reports for possible translation errors in a short space of time.

Where does the AI application offer the greatest benefit?

The preparation of annual reports is mandatory for many companies worldwide. In Germany, this includes stock corporations, partnerships limited by shares, cooperatives, credit institutions, public-law insurance companies and companies that meet the size criteria of the Disclosure Act. In certain cases, it may be necessary to translate the report from German into other languages. This applies, for example, if companies are active in the export business, if they have an international focus or if they are looking for local investors or business partners in other countries.

When translating such reports, it is essential that they are accurate and legally flawless. Accordingly, financial documents in particular require the utmost precision and care in order to avoid negative consequences. Until now, however, the translation and review of such documents has been a time-consuming, tedious process that is prone to errors. Overall, financial translations present specific challenges and require corresponding expertise in the financial sector. In addition to being susceptible to format errors, translations of annual reports are also particularly prone to semantic errors. The difference often seems minor and is not given much attention, but this can have serious consequences, especially as annual reports can be decisive for investments and shareholdings, for example.

What are the quality features of “Translation Check”?

  • Time savings: The KI.NRW demonstrator enables annual reports to be checked quickly and efficiently. With the help of AI models, text passages are checked and evaluated for content equivalents.
  • Integrated feedback and adaptability: The built-in feedback system allows users to evaluate the indications provided by the system. Based on the feedback, the model can then be further trained and the quality of the results continuously improved.
  • Overview and context: The integrated PDF viewer offers users the option of displaying any passages that are not consistent. In addition, all exam results can be exported as excel, which makes it easier to edit the documents later.
“Companies may need to translate their annual report from German into other languages. Translation Check uses AI models to support fast, efficient translation checking.”
Maren Pielka
Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS

Which AI technology is used in the KI.NRW demonstrator?

Language models

Modern language models are neural networks that are trained to predict a word based on its context. In this way, it learns an effective representation for all words in the text and is able to compare and classify text passages semantically.

Image recognition

PDF is a widely used unstructured file format. This means that although headings and tables are visually recognizable for readers, unlike .docx or .xlsx, for example, there is no structure that can be easily read automatically. In order to be able to work with PDFs automatically, intelligent image processing algorithms are required that extract this structure from the images and correctly classify objects such as tables and paragraphs.

What does the AI demonstrator show?

The AI-supported checking system is an intelligent, automated analysis of document translations. You can upload your own documents as well as have provided documents checked for possible translation errors such as format or tone.

Request a non-binding consultation with our experts now!

Curious? Click here to go straight to the demonstrator!

Where can I find more information?

AI.Map featuring entries in the field of data analysis and forecasting

More AI providers, applications, and AI products »made in NRW« with the same AI focus can be found using the filter and search function of the AI.Map, which currently contains more than 1300 entries.

Study on “Modern language technologies”

Find out where we encounter modern language technologies in everyday life and at work and what economic opportunities they offer.

Fraunhofer IAIS: Business unit Cognitive Business Optimization

Digitalisation in auditing, administration, controlling and more: Find out how you can efficiently analyse business documents and processes with the help of AI.

Contact the team of developers

Maren Pielka

Data Scientist and Team Leader Cognitive Text Analytics,
Business Area Cognitive Business Optimization,
Media Engineering Department

Fraunhofer IAIS
Schloss Birlinghoven
53757 Sankt Augustin

Phone +49 2241 14-2871

Send E-Mail

Tobias Deußer

Data Scientist
Geschäftsfeld Cognitive Business Optimization,
Abteilung Media Engineering

Fraunhofer IAIS
Schloss Birlinghoven
53757 Sankt Augustin

Telefon +49 2241 14-2303

Send E-Mail

AI-based diagnostic support in medicine with »Pneumo.AI«

»Pneumo.AI« is an AI-supported diagnostic software which supports medical professionals in the accurate identification of pneumonia using intelligent image recognition.

In which areas does the AI application offer the greatest benefit?

The »Pneumo.AI« demonstrator was developed to playfully illustrate the ways AI technologies and medical professionals can work together. The disease pneumonia, better known as lung inflammation, keeps specialized medical specialists busy in many hospitals. Until now, possible diseases had to be identified manually using X-ray images, among other things, to initiate appropriate treatment in good time. Today, image recognition systems can help with diagnosis. This not only saves time but can also prevent misjudgments.

What is pneumonia?

Pneumonia is an acute inflammation of the lower respiratory tract, commonly referred to as lung inflammation. Contrary to current belief, pneumonia is still a serious disease in many regions of the world today. In developing countries in particular, pneumonia is one of the most common causes of illness and death in children under the age of five.

How can AI help with diagnosis?

Artificial intelligence systems can support doctors in making a diagnosis. In this case, computer vision, i.e., machine vision, helps to recognize disease characteristics on chest scans.

What is the future of AI in medicine?

Both doctors and data scientists alike see great potential for AI in medicine. Many hospitals have large amounts of data available which could be used to improve diagnostic support. However, it is important that AI systems are only ever understood as assistance tools and that medical staff always remain in charge of decision-making. Also, medical data is highly sensitive and requires special protection.

What are »Pneumo.AI’s« quality characteristics?

  • Low effort: Since the annotation of medical image datasets usually involves a great deal of effort, it is important to develop data-efficient algorithms to achieve the lowest possible annotation effort.
  • Immediate analysis: The use of AI technologies allows for immediate evaluation of the scan/X-ray image after it has been taken – with no human interaction. This shows the potential to optimize work processes in clinics, for instance by developing a prioritization system. However, it is important that AI always serves as an assistance system for doctors and never makes decisions on its own.  
  • Secure data processing: For sensitive data such as patient data, it is essential that the AI processes used are secure. All data must be stored on German servers or may only be processed locally by medical specialists or in hospitals. 
  • Powerful AI: In the future, AI-based multimodal analysis will also play an important role in the evaluation of medical image data, as doctors will have a wide range of information available to them during the diagnostic process regarding the patient’s health status or the course of the disease.
»Close collaboration between medical experts and data scientists is the most important basis for the use of artificial intelligence in medicine.«
Helen Schneider
Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS

Which AI technology is used in the KI.NRW demonstrator?

Deep Learning

The Pneumo.AI demonstrator is based on deep convolutional neural networks (CNNs), which are particularly well suited for processing large image data sets. This technology can also be transferred to other diseases and use cases.

Informed Machine Learning

In this type of machine learning, available prior knowledge and expert knowledge are integrated into the model to develop more data-efficient algorithms, for instance. For Pneumo.AI, the elements of bilateral symmetry of the lung field were considered within the modeling.

Computer Vision

To ensure a good generalization capability of the trained network, various augmentation techniques are implemented. By rotating and zooming the training image data, the network achieves better performance and overfitting is avoided.

What does the AI demonstrator show?

The »Pneumo.AI« demonstrator shows how AI technologies can support doctors in practices and clinics in their everyday work in the future. It is important to emphasize that artificial intelligence is available to medical professionals as an assistance tool, but that the final decision remains with the human being. The demonstrator also illustrates the great potential of AI in medical image processing.

Request a non-binding consultation with our experts now!

Curious? Click here to go straight to the demonstrator!

Where can I find more information?

AI.Map featuring entries from the medical field

More AI providers, applications, and AI products »made in NRW« with the same AI focus can be found using the filter and search function of the AI.Map, which currently contains more than 1000 entries.

Lecture on Pneumo.AI at the MEDICA 2022 trade fair

At the international medical trade fair MEDICA 2022, KI.NRW and Fraunhofer IAIS gave a presentation on »Artificial intelligence in healthcare using the example of Pneumo.AI«.

SmartHospital: The use of AI in the hospital of the future

The KI.NRW flagship project SmartHospital.NRW aims at developing tools to support hospitals in their digital transformation and in the use of AI. Determine your hospital’s AI maturity level now.

Contact the team of developers

Helen Schneider

Data Scientist – Computer Vision

Fraunhofer IAIS
Schloss Birlinghoven
53757 Sankt Augustin

Phone +49 2241 14-2735

Send email

Dr. Rafet Sifa

Head of Cognitive Business Optimization

Fraunhofer IAIS
Schloss Birlinghoven
53757 Sankt Augustin

Phone +49 2241 14-2405

Send email

To the top