{"language":[{"iso":"eng"}],"user_id":"44006","date_updated":"2022-01-06T06:51:08Z","type":"conference","_id":"11744","status":"public","publication":"12. ITG Fachtagung Sprachkommunikation (ITG 2016)","citation":{"ieee":"A. Chinaev, J. Heymann, L. Drude, and R. Haeb-Umbach, “Noise-Presence-Probability-Based Noise PSD Estimation by Using DNNs,” in <i>12. ITG Fachtagung Sprachkommunikation (ITG 2016)</i>, 2016.","short":"A. Chinaev, J. Heymann, L. Drude, R. Haeb-Umbach, in: 12. ITG Fachtagung Sprachkommunikation (ITG 2016), 2016.","chicago":"Chinaev, Aleksej, Jahn Heymann, Lukas Drude, and Reinhold Haeb-Umbach. “Noise-Presence-Probability-Based Noise PSD Estimation by Using DNNs.” In <i>12. ITG Fachtagung Sprachkommunikation (ITG 2016)</i>, 2016.","bibtex":"@inproceedings{Chinaev_Heymann_Drude_Haeb-Umbach_2016, title={Noise-Presence-Probability-Based Noise PSD Estimation by Using DNNs}, booktitle={12. ITG Fachtagung Sprachkommunikation (ITG 2016)}, author={Chinaev, Aleksej and Heymann, Jahn and Drude, Lukas and Haeb-Umbach, Reinhold}, year={2016} }","apa":"Chinaev, A., Heymann, J., Drude, L., &#38; Haeb-Umbach, R. (2016). Noise-Presence-Probability-Based Noise PSD Estimation by Using DNNs. In <i>12. ITG Fachtagung Sprachkommunikation (ITG 2016)</i>.","mla":"Chinaev, Aleksej, et al. “Noise-Presence-Probability-Based Noise PSD Estimation by Using DNNs.” <i>12. ITG Fachtagung Sprachkommunikation (ITG 2016)</i>, 2016.","ama":"Chinaev A, Heymann J, Drude L, Haeb-Umbach R. Noise-Presence-Probability-Based Noise PSD Estimation by Using DNNs. In: <i>12. ITG Fachtagung Sprachkommunikation (ITG 2016)</i>. ; 2016."},"author":[{"full_name":"Chinaev, Aleksej","first_name":"Aleksej","last_name":"Chinaev"},{"last_name":"Heymann","id":"9168","first_name":"Jahn","full_name":"Heymann, Jahn"},{"last_name":"Drude","first_name":"Lukas","id":"11213","full_name":"Drude, Lukas"},{"full_name":"Haeb-Umbach, Reinhold","last_name":"Haeb-Umbach","id":"242","first_name":"Reinhold"}],"abstract":[{"text":"A noise power spectral density (PSD) estimation is an indispensable component of speech spectral enhancement systems. In this paper we present a noise PSD tracking algorithm, which employs a noise presence probability estimate delivered by a deep neural network (DNN). The algorithm provides a causal noise PSD estimate and can thus be used in speech enhancement systems for communication purposes. An extensive performance comparison has been carried out with ten causal state-of-the-art noise tracking algorithms taken from the literature and categorized acc. to applied techniques. The experiments showed that the proposed DNN-based noise PSD tracker outperforms all competing methods with respect to all tested performance measures, which include the noise tracking performance and the performance of a speech enhancement system employing the noise tracking component.","lang":"eng"}],"main_file_link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2016/ChHeyDrHa16.pdf","open_access":"1"}],"department":[{"_id":"54"}],"oa":"1","title":"Noise-Presence-Probability-Based Noise PSD Estimation by Using DNNs","related_material":{"link":[{"description":"Presentation","relation":"supplementary_material","url":"https://groups.uni-paderborn.de/nt/pubs/2016/ChHeyDrHa16_Presentation.pdf"}]},"date_created":"2019-07-12T05:27:25Z","year":"2016"}