Tobias Rosenkranz — accepted AI-conference papers

2022

Deepfilternet: A Low Complexity Speech Enhancement Framework for Full-Band Audio Based On Deep Filtering

Hendrik Schröter, Alberto N. Escalante-B., Tobias Rosenkranz, Andreas Maier

ICASSP 2022accepted

Complex-valued processing has brought deep learning-based speech enhancement and signal extraction to a new level. Typically, the process is based on a time-frequency (TF) mask which is applied to a noisy spectrogram, while complex masks (CM) are usually preferred over real-valued masks due to their…

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2020

CLCNET: Deep Learning-Based Noise Reduction for Hearing aids using Complex Linear Coding

Hendrik Schröter, Tobias Rosenkranz, Alberto N. Escalante-B., Marc Aubreville, Andreas K. Maier

ICASSP 2020accepted

Noise reduction is an important part of modern hearing aids and is included in most commercially available devices. Deep learning-based state-of-the-art algorithms, however, either do not consider real-time and frequency resolution constrains or result in poor quality under very noisy conditions.To…

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