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Foto: Universität Paderborn, Jörg Ullmann Show image information
Foto: Universität Paderborn, Jörg Ullmann Show image information
Foto: Universität Paderborn, Jörg Ullmann Show image information

Foto: Universität Paderborn, Jörg Ullmann

Foto: Universität Paderborn, Jörg Ullmann

Foto: Universität Paderborn, Jörg Ullmann

Source separation and interference reduction for automatic speech recognition in dynamic acoustic systems

This project is dedicated to a holistic approach for speech enhancement and recognition in an automatic house environment. Although, in recent years many advances in the field of automatic speech recognition (ASR) were made most cannot be applied in dynamic environments since they are burdened with high latencies and computational effort. Furthermore, most research on ASR is based on clean speech data without reverberation and multiple speakers which are essential parts of the acoustic signals in an automatic house

As a result a preprocessing system for speaker separation and interference reduction utilizing recurrent deep neuronal networks with low latency and small computational complexity is considered. To achieve best possible speech quality for the ASR system in an assumed automatic house environment a multi channel approach to speech enhancement using spectral masks is combined with different approaches to speaker separation. The resulting speech signal is examined on its usability in speech recognition and other applications in an automatic house.

This project is a financed by the “Deutsche Forschungsgemeinschaft” (DFG).

Contact

Jens Heitkämper

Communications Engineering

Research & Teaching

Jens Heitkämper
Phone:
+49 5251 60-5288
Fax:
+49 5251 60-3627
Office:
P7.2.06

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