no code implementations • 12 May 2022 • Mattes Ohlenbusch, Christian Rollwage, Simon Doclo
In this paper, we apply a deep learning-based bandwidth-extension system to the own voice reconstruction task and investigate different training strategies in order to overcome the limited availability of training data.
no code implementations • 15 Sep 2023 • Mattes Ohlenbusch, Christian Rollwage, Simon Doclo
To enhance the quality of the in-ear microphone signal using algorithms aiming at joint bandwidth extension, equalization, and noise reduction, it is desirable to have an accurate model of the own voice transfer characteristics between the entrance of the ear canal and the in-ear microphone.
no code implementations • 10 Oct 2023 • Mattes Ohlenbusch, Christian Rollwage, Simon Doclo
In this paper, we propose a speech-dependent model of the own voice transfer characteristics based on phoneme recognition, assuming a linear time-invariant relative transfer function for each phoneme.
no code implementations • 14 Dec 2023 • Mattes Ohlenbusch, Christian Rollwage, Simon Doclo
Recording a sufficient amount of noise required for training such a system is costly since noise transmission between outer and inner microphones varies individually.