activity
20222026
most citedTraining Strategies for Own Voice Reconstruction in Hearing Protection Devices using an In-ear Microphone

9 citations · 28 across the 10 of their papers we have counts for

collaborators

10 papers

eess.AS2026

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…

eess.AS2025

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…

eess.AS2025

PAS-SE: Personalized Auxiliary-Sensor Speech Enhancement for Voice Pickup in Hearables

Mattes Ohlenbusch, Mikolaj Kegler, Marko Stamenovic

Speech enhancement for voice pickup in hearables aims to improve the user's voice by suppressing noise and interfering talkers, while maintaining own-voice quality. For single-chan…

eess.AS2025

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…

eess.AS2024★ 2 cited

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…

eess.AS2024

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…

eess.AS2023★ 6 cited

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…

eess.AS2023★ 8 cited

Modeling of Speech-dependent Own Voice Transfer Characteristics for Hearables with In-ear Microphones

Mattes Ohlenbusch, Christian Rollwage, Simon Doclo

Many hearables contain an in-ear microphone, which may be used to capture the own voice of its user. However, due to the hearable occluding the ear canal, the in-ear microphone mos…

eess.AS2023★ 3 cited

Speech-dependent Modeling of Own Voice Transfer Characteristics for In-ear Microphones in Hearables

Mattes Ohlenbusch, Christian Rollwage, Simon Doclo

Many hearables contain an in-ear microphone, which may be used to capture the own voice of its user in noisy environments. Since the in-ear microphone mostly records body-conducted…

eess.AS2022★ 9 cited

Training Strategies for Own Voice Reconstruction in Hearing Protection Devices using an In-ear Microphone

Mattes Ohlenbusch, Christian Rollwage, Simon Doclo

In-ear microphones in hearing protection devices can be utilized to capture the own voice speech of the person wearing the devices in noisy environments. Since in-ear recordings of…