CLCNet: Deep learning-based noise reduction for hearing aids using complex linear coding

Schröter H, Rosenkranz T, Escalante Banuelos A, Aubreville M, Maier A (2020)

Publication Language: English

Publication Type: Conference contribution, Conference Contribution

Publication year: 2020

Conference Proceedings Title: ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Event location: Barcelona ES

URI: https://rikorose.github.io/CLCNet-audio-samples.github.io/

DOI: 10.1109/icassp40776.2020.9053563

Open Access Link: https://arxiv.org/abs/2001.10218

Abstract

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 improve monaural speech enhancement in noisy environments, we propose CLCNet, a framework based on complex valued linear coding. First, we define complex linear coding (CLC) motivated by linear predictive coding (LPC) that is applied in the complex frequency domain. Second, we propose a framework that incorporates complex spectrogram input and coefficient output. Third, we define a parametric normalization for complex valued spectrograms that complies with low-latency and on-line processing. Our CLCNet was evaluated on a mixture of the EUROM database and a real-world noise dataset recorded with hearing aids and compared to traditional real-valued Wiener-Filter gains.

Authors with CRIS profile

Hendrik Schröter Lehrstuhl für Informatik 5 (Mustererkennung) Marc Aubreville Lehrstuhl für Informatik 14 (Bild- und Sprachverarbeitung) (LME) Andreas Maier Lehrstuhl für Informatik 5 (Mustererkennung)

Additional Organisation(s)

Lehrstuhl für Informatik 14 (Bild- und Sprachverarbeitung) (LME)

Related research project(s)

Deep Learning based Noise Reduction for Hearing Aids Feb. 1, 2019 - Jan. 31, 2023

Involved external institutions

Sivantos GmbH DE Germany (DE)

How to cite

APA:

Schröter, H., Rosenkranz, T., Escalante Banuelos, A., Aubreville, M., & Maier, A. (2020). CLCNet: Deep learning-based noise reduction for hearing aids using complex linear coding. In ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Barcelona, ES.

MLA:

Schröter, Hendrik, et al. "CLCNet: Deep learning-based noise reduction for hearing aids using complex linear coding." Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Barcelona 2020.

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