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eess.AS2024
Comparative Analysis Of Discriminative Deep Learning-Based Noise Reduction Methods In Low SNR Scenarios
Shrishti Saha Shetu, Emanuël A. P. Habets, Andreas Brendel
In this study, we conduct a comparative analysis of deep learning-based noise reduction methods in low signal-to-noise ratio (SNR) scenarios. Our investigation primarily focuses on…
eess.AS2024
Blind Acoustic Parameter Estimation Through Task-Agnostic Embeddings Using Latent Approximations
Philipp Götz, Cagdas Tuna, Andreas Brendel +2
We present a method for blind acoustic parameter estimation from single-channel reverberant speech. The method is structured into three stages. In the first stage, a variational au…
eess.AS2023
End-To-End Deep Learning-based Adaptation Control for Linear Acoustic Echo Cancellation
Thomas Haubner, Andreas Brendel, Walter Kellermann
The attenuation of acoustic loudspeaker echoes remains to be one of the open challenges to achieve pleasant full-duplex hands free speech communication. In many modern signal enhan…