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Improved graph-based SFA: information preservation complements the slowness principle.

, and . Mach. Learn., 109 (5): 999-1037 (2020)

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CLCNET: Deep Learning-Based Noise Reduction for Hearing aids using Complex Linear Coding., , , , and . ICASSP, page 6949-6953. IEEE, (2020)Deepfilternet2: Towards Real-Time Speech Enhancement on Embedded Devices for Full-Band Audio., , , and . IWAENC, page 1-5. IEEE, (2022)Measuring the Data Efficiency of Deep Learning Methods., , and . ICPRAM, page 691-698. SciTePress, (2019)Deepfilternet: A Low Complexity Speech Enhancement Framework for Full-Band Audio Based On Deep Filtering., , , and . ICASSP, page 7407-7411. IEEE, (2022)DeepFilterNet: Perceptually Motivated Real-Time Speech Enhancement., , , and . INTERSPEECH, page 2008-2009. ISCA, (2023)Theoretical Analysis of the Optimal Free Responses of Graph-Based SFA for the Design of Training Graphs., and . J. Mach. Learn. Res., (2016)Deep Multi-Frame Filtering for Hearing Aids., , , and . INTERSPEECH, page 3869-3873. ISCA, (2023)Improved graph-based SFA: information preservation complements the slowness principle., and . Mach. Learn., 109 (5): 999-1037 (2020)LACOPE: Latency-Constrained Pitch Estimation for Speech Enhancement., , , and . Interspeech, page 656-660. ISCA, (2021)Fricative Phoneme Detection Using Deep Neural Networks and its Comparison to Traditional Methods., , , , , and . Interspeech, page 51-55. ISCA, (2021)