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Gburrek, Tobias, et al. “Deep Neural Network Based Distance Estimation for Geometry Calibration in Acoustic Sensor Network.” European Signal Processing Conference (EUSIPCO), 2020.
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Ebbers, Janek, and Reinhold Haeb-Umbach. “Forward-Backward Convolutional Recurrent Neural Networks and Tag-Conditioned Convolutional Neural Networks for Weakly Labeled Semi-Supervised Sound Event Detection.” Proceedings of the Detection and Classification of Acoustic Scenes and Events 2020 Workshop (DCA), 2020.
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Drude, Lukas, and Reinhold Haeb-Umbach. “Integration of Neural Networks and Probabilistic Spatial Models for Acoustic Blind Source Separation.”10.1109/JSTSP.2019.2912565__IEEE Journal of Selected Topics in Signal Processing, 2019, doi:10.1109/JSTSP.2019.2912565.
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von Neumann, Thilo, et al. “All-Neural Online Source Separation, Counting, and Diarization for Meeting Analysis.” ICASSP 2019, Brighton, UK, 2019.
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Haeb-Umbach, Reinhold, et al. “Speech Processing for Digital Home Assistance: Combining Signal Processing With Deep-Learning Techniques.”10.1109/MSP.2019.2918706__IEEE Signal Processing Magazine, vol. 36, no. 6, 2019, pp. 111–24, doi:10.1109/MSP.2019.2918706.
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Haeb-Umbach, Reinhold. “Lektionen Für Alexa &; Co?!”10.1002/fors.201970104__DFG Forschung 1/2019, 2019, pp. 12–15, doi:10.1002/fors.201970104.
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Ebbers, Janek, and Reinhold Haeb-Umbach. “Convolutional Recurrent Neural Network and Data Augmentation for Audio Tagging with Noisy Labels and Minimal Supervision.” DCA Workshop, New York, USA, 2019.
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