67 citations · 101 across the 8 of their papers we have counts for
8 papers
Align-ULCNet: Towards Low-Complexity and Robust Acoustic Echo and Noise Reduction
Shrishti Saha Shetu, Naveen Kumar Desiraju, Wolfgang Mack +1
The successful deployment of deep learning-based acoustic echo and noise reduction (AENR) methods in consumer devices has spurred interest in developing low-complexity solutions, w…
Multi-Microphone Speaker Separation by Spatial Regions
Julian Wechsler, Srikanth Raj Chetupalli, Wolfgang Mack +1
We consider the task of region-based source separation of reverberant multi-microphone recordings. We assume pre-defined spatial regions with a single active source per region. The…
Speaker Verification in Multi-Speaker Environments Using Temporal Feature Fusion
Ahmad Aloradi, Wolfgang Mack, Mohamed Elminshawi +1
Verifying the identity of a speaker is crucial in modern human-machine interfaces, e.g., to ensure privacy protection or to enable biometric authentication. Classical speaker verif…
New Insights on Target Speaker Extraction
Mohamed Elminshawi, Wolfgang Mack, Srikanth Raj Chetupalli +2
Speaker extraction (SE) aims to segregate the speech of a target speaker from a mixture of interfering speakers with the help of auxiliary information. Several forms of auxiliary i…
Signal-Aware Direction-of-Arrival Estimation Using Attention Mechanisms
Wolfgang Mack, Julian Wechsler, Emanuël A. P. Habets
The direction-of-arrival (DOA) of sound sources is an essential acoustic parameter used, e.g., for multi-channel speech enhancement or source tracking. Complex acoustic scenarios c…
Efficient Training Data Generation for Phase-Based DOA Estimation
Fabian Hübner, Wolfgang Mack, Emanuël A. P. Habets
Deep learning (DL) based direction of arrival (DOA) estimation is an active research topic and currently represents the state-of-the-art. Usually, DL-based DOA estimators are train…
Informed Source Extraction With Application to Acoustic Echo Reduction
Mohamed Elminshawi, Wolfgang Mack, Emanuël A. P. Habets
Informed speaker extraction aims to extract a target speech signal from a mixture of sources given prior knowledge about the desired speaker. Recent deep learning-based methods lev…
Deep Filtering: Signal Extraction and Reconstruction Using Complex Time-Frequency Filters
Wolfgang Mack, Emanuël A. P. Habets
Signal extraction from a single-channel mixture with additional undesired signals is most commonly performed using time-frequency (TF) masks. Typically, the mask is estimated with…