Data analysis and forecasting

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

Advantages

Precision & Quality
Process optimization
Real-time results 24/7
Time efficiency & Agility
Workload relief / Comfort

Functional areas

Assistance / Support / Staff positions
Finances / Law

To the demonstrator

→ Translation Check

To overview

“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!

Try it out now

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.

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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.

To the study (DE)

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.

To the Website (DE)

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

Data analysis and forecasting

“Sustain.AI” – The AI tool for analyzing sustainability reports

Advantages

Creativity & Innovation
Energy efficiency
Expense & Revenue Optimization
Knowledge & Complexity reduction
Materials efficiency
Precision & Quality
Real-time results 24/7
Time efficiency & Agility

Functional areas

Assistance / Support / Staff positions
Finances / Law

To the demonstrator

→ Sustain.AI

To overview

“Sustain.AI” – The AI tool for analyzing sustainability reports

Where does the AI application offer the greatest benefit?

Sustainability reports are an important part of a company’s information policy. They provide interested members of the public with information about the organization’s activities and performance regarding sustainable development. Since 2017, all listed companies with 500 or more employees have been required to publish such reports. In doing so, they follow the CSR (Corporate Social Responsibility) directive. The main aim of this directive is to increase transparency regarding the environmental and social aspects of companies in the EU. This includes information on environmental, social and employee issues as well as the protection of human rights and the fight against corruption.

Like annual reports, sustainability reports are also used as a basis for important purchasing or investment decisions. However, the necessary identification of all relevant criteria and information usually requires a great deal of time and effort. With the tightening of the CSR Directive implemented by the EU in 2023, which will extend reporting requirements to other aspects and a larger group of companies, this work becomes even more complex – especially if reports are evaluated manually.

The AI-based tool Sustain.AI makes this work easier. Thanks to machine text recognition, sustainability reports can now be analyzed in a highly efficient and structured way. The technology behind Sustain.AI is particularly aimed at auditors and controllers who can use the tool in their day-to-day work.

What are “Sustain.AI’s” quality features?

Time saving: The KI.NRW demonstrator allows for quick and efficient handling of sustainability reports and analysis of the required CSR criteria. With the help of AI language models, the text passages relevant to the respective criteria are filtered out. In this way, auditors can focus on the sections that are most relevant to the respective criterion.
Overview and context: With the integrated PDF viewer, the extracted text elements can be displayed in the report at any time. This allows users to immediately grasp the context of the passage.
Integrated feedback and adaptability: Users can evaluate the system’s suggestions using the built-in feedback system. This helps us to further train the AI model and continuously improve its quality. It is also capable of learning new criteria.

“Sustainability is increasingly becoming the focus of public attention. With the AI-supported tool Sustain.AI, it is possible to efficiently analyze and browse sustainability reports.”

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 which are trained to predict a word by the context in which it appears. In this way, they learn an accurate representation for all words in the text and is capable of semantically comparing and classifying text passages.

Image recognition

PDF is a widely used unstructured file format. This means that although headings and tables are visually recognizable to readers, there is no internal structure. To be able to work with PDFs automatically, intelligent image processing algorithms are required to extract this structure from the images and correctly classify objects such as tables and paragraphs.

What does the AI demonstrator show?

The AI-supported suggestion system is an intelligent, intuitive search engine. You can upload your own documents as well as view existing reports. The reports can be searched and analyzed using a stored checklist from the “Global Reporting Initiative”, a widely used reporting framework for sustainability reporting.

Request a non-binding consultation with our experts now!

Curious? Click here to go straight to the demonstrator!

Try it out now!

Where can I find more information?

AI.map with entries around 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 1000 entries.

Go to the AI.Map

Study “Modern language technologies”

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

Go to the study

Fraunhofer IAIS: Media Engineering

You can learn more about the topics of “Cognitive Business Optimization”, “Smart Coding and Learning”, and AI-based industrial image processing on the website of the IAIS Media Engineering department.

Go to the website

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 email

Lars Patrick Hillebrand

PhD Student / Research Assistant in Machine Learning,
Media Engineering Department

Fraunhofer IAIS
Schloss Birlinghoven
53757 Sankt Augustin

Phone +49 2241 14-1920

Send email

Speech and text comprehension

Roberta SPEAKER – Easily design your own dialog assistant

Advantages

Creativity & Innovation
Knowledge & Complexity reduction
Time efficiency & Agility

Functional areas

Marketing / Sales
Support / Customer service

To the demonstrator

→ Go to the »Roberta SPEAKER« clip

To overview

Roberta SPEAKER – Easily design your own dialog assistant

Develop your own dialog assistant in an intuitive way – with the visual, no-code programming interface »Open Roberta®«!

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

Speech technologies play a key role in the development of new digital services and technologies and already serve as a reliable assistant at home. Whether Alexa or Siri, voice communication with computers has long since arrived in everyday life: A quick question about the likelihood of rain or the risk of traffic jams on the way home, as well as controlling music or lights within your own four walls – communication with voice assistants is becoming increasingly common. But how can voice assistants be used in companies or even in schools?

Data-secure, customized – Roberta SPEAKER for companies and in education

The KI.NRW demonstrator »Roberta SPEAKER« allows even programming novices to develop dialog functions easily and intuitively on their own. Users from different industries can benefit from this: The technology enables companies to develop their own dialog assistants, for instance to control their machines via voice commands. In addition to the autonomous design of the dialogs, the advantages also include data security, because unlike many commercial voice assistants, Roberta SPEAKER does not require an internet connection – all data is processed locally. Teachers and educational stakeholders will also be able to use Roberta SPEAKER in the future to better teach young people about the use of AI technologies in everyday life and build their digital skills.

The programming language for dialog control is NEPO®, which is assembled on the open-source platform Open Roberta from Fraunhofer IAIS using »drag and drop«, thus avoiding obstacles such as typing or syntax errors. The speech recognition model can be adapted specifically to the user’s own requirements and thus run on a microcomputer. As a result, there is no need for expensive and complex hardware. For the communication between users and voice assistants, additional elements such as a microphone and speakers are also included.

The demonstrator was developed as part of the SPEAKER project funded by the German Federal Ministry for Economic Affairs and Climate Action (BMWK). The SPEAKER project aims to establish a leading voice assistance platform »made in Germany« for business-to-business (B2B) applications. The platform is intended to be open, modular, and scalable and provide technologies, services, and data via service interfaces. The consortium leaders are the Fraunhofer Institutes IAIS and IIS.

What are Roberta SPEAKER’s quality characteristics?

Low effort: The KI.NRW demonstrator shows that AI language models can work even on a small (portable) processor. This opens up innovative functional possibilities. One of the benefits is that the AI models work locally, so there is no need for an internet connection. This way, the Roberta SPEAKER box demonstrates that voice assistants can be implemented almost anywhere to interact with people and carry out simple tasks with little effort.
Intuitive and individually customizable: The intuitive programming interface allows everyone to easily develop functioning program sequences, so that students can generate their own voice commands using the demonstrator. The programming interface is the Open Roberta Lab, a freely available, data-secure, and open programming platform developed by the educational initiative »Roberta® – Learning with Robots« by Fraunhofer IAIS.
Easy communication: By using artificial intelligence, users can communicate with the voice assistants via spoken language. The dialog assistant understands questions and commands, can derive actions from the user’s intentions and can formulate answers and communicate these via the loudspeaker or derive actions.
Powerful and resource-saving: The voice-controlled box is only ready for use when the artificial intelligence technologies, the AI models, can function on a small processor. This is why the developers are focusing on resource-saving AI technology.

»Dialog systems are everywhere. With ›Roberta Speaker‹, we make it possible for anyone to create their own dialogs to control IoT devices using drag-and-drop with almost no prior knowledge.«

Thorsten Leimbach

Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS

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

Automated Speech Recognition (ASR)

Technical systems capable of understanding spoken commands allow for natural communication between humans and machines. Speech recognition reliably converts spoken information into digital text in real time – even under difficult conditions, such as when there is background noise, as can occur in an industrial environment, for example, or when regional dialects are spoken.

Intent Recognition

Only domain-specific knowledge makes the language system useful in certain areas of application. Intent recognition, the recognition of intentions from the spoken text, plays a key role here. An intent classifier recognizes the subject of the text and searches for the factual answer. With the help of verbalization techniques, the system then ensures that the response is fully formulated.

Text-to-Speech (TTS)

In human-machine interaction, it is often an advantage when text information does not have to be read, from a display for instance, but is transmitted using natural speech. Based on deep learning technology, state-of-the-art algorithms generate highly natural-sounding speech output with excellent intelligibility and fluent intonation.

What does the AI demonstrator show?

The KI.NRW demonstrator »Roberta SPEAKER« allows both companies and students from different types of schools, such as secondary schools or vocational schools, to develop their own voice assistant using a simple programming interface. In this way, the expression »do it yourself« is given a new meaning and people can start learning about AI technologies without any prior knowledge.

Request a non-binding consultation with our experts now!

Where can I find more information?

Study »Modern language technologies«

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

Go to the study

Roberta SPEAKER for companies

Are you interested in using Roberta SPEAKER to conduct AI trainings in your company or would you like to know how you can integrate the Fraunhofer language technology into your processes?

Enquire now!

Roberta SPEAKER in education

Do you want to use Roberta SPEAKER in an educational context?

Enquire now!

Contact the team of developers

Thorsten Leimbach

Head of Smart Coding and Learning

Fraunhofer IAIS
Schloss Birlinghoven
53757 Sankt Augustin

Phone +49 2241 142404

send email

Beate Jost

Technical Manager at Roberta

Fraunhofer IAIS
Schloss Birlinghoven
53757 Sankt Augustin

Phone +49 2241 142441

send email

Dr.-Ing. Oliver Walter

Team leader
Real Time Speech Recognition

Fraunhofer IAIS
Schloss Birlinghoven
53757 Sankt Augustin

Phone +49 2241 2541

send email

Image recognition and understanding

Image-based quality control “Damage Detection”

Advantages

Precision & Quality
Relief & Comfort
Time efficiency & Agility

Functional areas

Production / Assembly
Storage / Logistics

To the demonstrator

→ To the movie about "Damage Detection"

To overview

Image-based quality control “Damage Detection”

Automated inspection of damage and defects using AI-assisted quality control of reflective surfaces.

Where does the AI application offer the greatest benefit?

The inspection of reflective surfaces, for example of quality defects in production or damage to vehicles, is often still carried out manually and therefore turns out to be time-consuming and requires a high level of expertise on the part of the persons in charge. In order to increase the productivity of the processes, “Damage Detection”, an AI system for the quality control of shiny or diffusely reflecting surfaces, has been developed. It is suitable for a wide range of applications: from industrial production, for example in the automotive industry, to the leasing and insurance industry and to automotive appraisals. The system works automatically and takes less than a minute for surface inspection. The quality defects found are categorized using Deep Learning. The combination of deflectometry, i.e. the contact-free detection of reflective surfaces, conventional image recognition processes and artificial intelligence methods is a unique system.

What are the quality indicators of such AI applications?

“Damage Detection” offers low hardware and maintenance costs as a solution. The AI application can be used flexibly and retrofitted into existing productions. Among other things, the solution is able to work under the influence of stray light (e.g. ceiling lighting in a production hall).
The system delivers 100% test coverage. It combines high accuracy with low hardware requirements. Currently, defects as small as 0.1 mm can be detected on 1 m component size.
By using Artificial Intelligence, the system can be trained to detect various types of defects on the surface.
In addition to highly reflective surfaces, the latest developments also allow diffusely reflective surfaces to be tested for their quality.

“The combination of conventional image recognition
methods, AI methods and the detection of reflective
surfaces is unique.”

Dr. rer. nat. Theresa Bick

Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS

What AI technology powers the demonstrator of KI.NRW?

Computer Vision

The solution relies on Convolutional Neural Networks (CNNs) for detection and classification of the surface anomalies. The CNN model belongs to the Artificial Neural Networks, which are suitable for image recognition and understanding.

Informed Machine Learning

By incorporating expert knowledge, the system is able to make dataintensive neural networks practical for industrial production. The amount of training data and the annotation effort can be kept comparatively low.

Combination with classical image processing

The AI is linked to classical image processing. The system uses the advantages of both worlds – fast, approximate algorithms from classical image processing and the powerful methods of deep learning.

What does the AI demonstrator show?

Quality control of shiny or diffusely reflecting surfaces is notable for its simple, mobile hardware design. It operates independently of ambient light and is fully automated. It takes less than one minute for a surface inspection.