Source separation and noise reduction for automatic speech recognition in dynamic acoustic scenarios

• Applicant: Professor Dr.-Ing. Reinhold Häb-Umbach
• Subject Area: Electronic Semiconductors, Components and Circuits, Integrated Systems, Sensor Technology, Theoretical Electrical Engineering ; Image and Language Processing, Computer Graphics and Visualisation, Human Computer Interaction, Ubiquitous and Wearable Computing
• Term: from 2016 to 2021
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 316471544

The goal of the project is the development of an automatic speech recognition system to be used for hands-free voice control in a smart home environment. Starting with the multi-channel blind source separation and noise reduction techniques developed in the DFG-funded preceding project, these algorithms will be further developed and optimized with respect to latency and realizability on resource-constrained embedded hardware. The prototyp to be developed shall perform recognition in real-time with low latency and achieve superior recognition rates in acoustic environments typical of smart home applications compared to an existing speech recognition system available at the industrial partner.As an alternative to the above parametric source separation and speech enhancement algorithms, we will also research and develop neural network based solutions. We will carry out a thorough comparison between the two approaches with respect to enhancement/recogntion performance, latency, computational and memory requirements and robustness towards varying acoustic environmental conditions.

• DFG Programme: Research Grants (Transfer Project)
• Application Partner: voice INTER connect GmbH