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Laboratory for Audio Communication and Acoustics

In the Laboratory for Audio Communication and Acoustics, students learn about digital audio signal and image processing as well as machine learning and artificial intelligence.

Research activities focus on the application-oriented development of artificial intelligence for signal processing, signal evaluation and sensor data utilisation.

Research and Transfer

The research areas in the Laboratory for Audio Communication and Acoustics include speech enhancement, predictive maintenance, human-machine interaction and acoustic environment perception.

  • Speech Enhancement

    Research is underway to develop methods for enhancing speech sinals using artificial intelligence (AI) to improve speech intelligibility and quality in acoustic conditions where conventional algorithms often reach their limits. These innovative methods are frequently combined with classical algorithms to achieve the best possible results.

    Uses:

    • Voice control
    • Text-to-speech
    • In-car communication (ICC)
    • Smartphones
    • Smart homes
    • Medicine (e.g. operating tables)
    • Care (e.g. care beds)
    • Industry (e.g. manufacturing)
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  • Predictive Maintenance

    Predictive maintenance with artificial intelligence (AI) involves the early detection of critical machine conditions. Sensors monitor the state of a machine, and the AI analyses this data to schedule maintenance proactively, preventing unexpected breakdowns. This approach aims to enhance sustainability and cost-effectiveness while providing advantages over traditional maintenance intervals.

    Uses:

    • Correctly assess system status
    • Routine maintenance as required
    • Recognise critical machine conditions
    • Avoid sudden machine failures
    • Avoid expensive production stops
    • Evaluate large amounts of data from sensors with AI
    •

  • Human-Machine Interaction

    New interaction options, such as gesture or voice control, along with facil recognition using artificial intelligence (AI), are at the forefront of this research. In contrast to conventional methods for controlling devices, this approach allows data to be collected and control commands to be transferred while the operator carries out another activity. The aim is to increase convenience, efficiency and safety. Sensor data fusion also plays a key role in this process.

    Uses:

    Driver State Monitoring Systems: These are able to determine the driver's condition and increase safety while driving by providing information or directly intervening in what is happening. Relevant impairments are, for example, physical impairment, fatigue, alcohol or drug consumption, distraction, unexpected and sudden illness. In addition the detection of emotions, stress levels, health, speaker verification for access control are other valuable applications in vehicles.

    •

  • Acoustic Environment Perception

    To increase road safety, vehicles will learn to hear in the future. In Acoustic Environment Perception, acoustic events outside the vehicle are recorded using airborne sound microphone arrays and processed in real time by an intelligent signal processing unit. The recognition of different events and hazardous situations outside the vehicle is realised with the help of artificial intelligence and machine learning techniques.

    Uses:


    Detection of an approaching siren:

    • Display on the dashboard to form an emergency lane in good time.
    • Switching on the hazard warning flashers and initiating an evasive manoeuvre.
    • Automatic reduction of the volume of the car hi-fi system.

      Condition monitoring of the vehicle based on driving noise:
    • early detection of critical signs of wear and tear.
    • Detection of fault conditions due to unusual driving noises (e.g. nail in tyre).

      Audio-visual detection:
    • Hazardous situations: Play road, pedestrian and cycle paths.
    • Driver gives instructions, e.g. for parking, unparking or re-parking an autonomous vehicle.
    •

Thesis Work

In the Laboratory for Audio Communication and Acoustics, final theses from the various research fields can be worked on.

In the video on voice control of a robot, our students show you how the directional effect of sound can be used to mask a sound source. Are you interested in writing your student research project, bachelor's thesis or master's thesis in the Laboratory for Audio Communication and Acoustics? - Please feel free to contact us.

Projects

  • Connection Concepts through gaming workshop

    ConnectS UP

    The ConnectS UP project promotes the connection between universities and companies through innovative, practical teaching methods.

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  • STEPS4EU Kick-off-Meeting in Mailand

    ERASMUS+ Project STEPS4EU

    Improvement of the overall success of engineering projects in the EU through the development of cross-functional skills of all participating team members.

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  • The Primavera24 presenter interviews Prof. Dr. Rainer Georg Hofmann.

    mainproject

    Information transfer project focusing on digital transformation, sustainability and agile transition to strengthen the competitiveness of SMEs enterprises in the Bavarian Lower Main region.

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  • AI modelling with expert knowledge for Indusrtry workspaces

    Exkimo

    AI modelling with integration of expert knowledge for use in industrial processes.

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  • A student sits in a research vehicle at the TH Aschaffenburg.

    i4Driving: Integrated 4D driving modelling with consideration of uncertainties

    Development of a database that expands, integrates, and provides several reference models to represent the diversity of human driving behavior for virtual CCAM evaluation.

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  • Zwei Forscher stehen vor ihrem Forschungsprojekt

    MOSES

    Multi-optical sensor technology and real-time data processing are used to capture the process situation for automated UKP laser based PCB processing for manufacturing inductive sensors of the future.

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  • International Mercuri students at the TH Aschaffenburg campus

    MERCURI

    Development of a transnational study programme in Customer Relationship Marketing, in collaboration with four universties.

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  • Gebäudemauer am Campus 1

    dima Digital Manufactory

    The Digital Manufacture supports citizens of the city of Aschaffenburg with applied artificial intelligence to improve the urban living space.

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  • Prof. Dr. Erich Ruppert und Joachim Schmitt referieren im Rahmen des Wissenstransferprojekts mainproject.

    TransferformKMU

    With TransferformKMU, the Institute for Management and leadership supports regional companies on their way out of the pandemic with further training on sustainability and transformation.

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  • The European Central Bank Euro Symbol in Frankfurt

    Quantitative Easing

    In January 2015, the ECB Governing Council decided on the "Quantitative Easing" asset purchase programme. The project comments on this decision and the resulting consequences.

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