Laboratory for Audio Communication and Acoustics

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.

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.

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.

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.