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Improving acoustic drone detection generalization through pretraining and data augmentation
Paul M. Reuter, Mattes Ohlenbusch, Christian Rollwage
Detecting unauthorized UAV flights is critical for surveillance, security, and airspace management. Acoustic drone detection, which relies on the distinctive propeller and motor so…
Subjective quality evaluation of personalized own voice reconstruction systems
Mattes Ohlenbusch, Christian Rollwage, Simon Doclo +1
Own voice pickup technology for hearable devices facilitates communication in noisy environments. Own voice reconstruction (OVR) systems enhance the quality and intelligibility of…
Comparison of Knowledge Distillation Methods for Low-complexity Multi-microphone Speech Enhancement using the FT-JNF Architecture
Robert Metzger, Mattes Ohlenbusch, Christian Rollwage +1
Multi-microphone speech enhancement using deep neural networks (DNNs) has significantly progressed in recent years. However, many proposed DNN-based speech enhancement algorithms c…
Low-Complexity Own Voice Reconstruction for Hearables with an In-Ear Microphone
Mattes Ohlenbusch, Christian Rollwage, Simon Doclo
Hearable devices, equipped with one or more microphones, are commonly used for speech communication. Here, we consider the scenario where a hearable is used to capture the user's o…
Speech-dependent Data Augmentation for Own Voice Reconstruction with Hearable Microphones in Noisy Environments
Mattes Ohlenbusch, Christian Rollwage, Simon Doclo
Own voice pickup for hearables in noisy environments benefits from using both an outer and an in-ear microphone outside and inside the occluded ear. Due to environmental noise reco…
Multi-Microphone Noise Data Augmentation for DNN-based Own Voice Reconstruction for Hearables in Noisy Environments
Mattes Ohlenbusch, Christian Rollwage, Simon Doclo
Hearables with integrated microphones may offer communication benefits in noisy working environments, e.g. by transmitting the recorded own voice of the user. Systems aiming at rec…