{"publication":"ITG 2018, Oldenburg, Germany","date_updated":"2022-01-06T06:51:11Z","type":"conference","main_file_link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2018/ITG_2018_Drude_Paper.pdf","open_access":"1"}],"language":[{"iso":"eng"}],"date_created":"2019-07-12T05:29:54Z","citation":{"chicago":"Drude, Lukas, Jahn Heymann, Christoph Boeddeker, and Reinhold Haeb-Umbach. “NARA-WPE: A Python Package for Weighted Prediction Error Dereverberation in Numpy and Tensorflow for Online and Offline Processing.” In <i>ITG 2018, Oldenburg, Germany</i>, 2018.","apa":"Drude, L., Heymann, J., Boeddeker, C., &#38; Haeb-Umbach, R. (2018). NARA-WPE: A Python package for weighted prediction error dereverberation in Numpy and Tensorflow for online and offline processing. In <i>ITG 2018, Oldenburg, Germany</i>.","short":"L. Drude, J. Heymann, C. Boeddeker, R. Haeb-Umbach, in: ITG 2018, Oldenburg, Germany, 2018.","ieee":"L. Drude, J. Heymann, C. Boeddeker, and R. Haeb-Umbach, “NARA-WPE: A Python package for weighted prediction error dereverberation in Numpy and Tensorflow for online and offline processing,” in <i>ITG 2018, Oldenburg, Germany</i>, 2018.","ama":"Drude L, Heymann J, Boeddeker C, Haeb-Umbach R. NARA-WPE: A Python package for weighted prediction error dereverberation in Numpy and Tensorflow for online and offline processing. In: <i>ITG 2018, Oldenburg, Germany</i>. ; 2018.","mla":"Drude, Lukas, et al. “NARA-WPE: A Python Package for Weighted Prediction Error Dereverberation in Numpy and Tensorflow for Online and Offline Processing.” <i>ITG 2018, Oldenburg, Germany</i>, 2018.","bibtex":"@inproceedings{Drude_Heymann_Boeddeker_Haeb-Umbach_2018, title={NARA-WPE: A Python package for weighted prediction error dereverberation in Numpy and Tensorflow for online and offline processing}, booktitle={ITG 2018, Oldenburg, Germany}, author={Drude, Lukas and Heymann, Jahn and Boeddeker, Christoph and Haeb-Umbach, Reinhold}, year={2018} }"},"related_material":{"link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2018/ITG_2018_Drude_Poster.pdf","description":"Poster","relation":"supplementary_material"}]},"user_id":"40767","department":[{"_id":"54"}],"_id":"11873","title":"NARA-WPE: A Python package for weighted prediction error dereverberation in Numpy and Tensorflow for online and offline processing","oa":"1","author":[{"id":"11213","last_name":"Drude","full_name":"Drude, Lukas","first_name":"Lukas"},{"first_name":"Jahn","full_name":"Heymann, Jahn","id":"9168","last_name":"Heymann"},{"id":"40767","last_name":"Boeddeker","full_name":"Boeddeker, Christoph","first_name":"Christoph"},{"last_name":"Haeb-Umbach","id":"242","full_name":"Haeb-Umbach, Reinhold","first_name":"Reinhold"}],"abstract":[{"lang":"eng","text":"NARA-WPE is a Python software package providing implementations of the weighted prediction error (WPE) dereverberation algorithm. WPE has been shown to be a highly effective tool for speech dereverberation, thus improving the perceptual quality of the signal and improving the recognition performance of downstream automatic speech recognition (ASR). It is suitable both for single-channel and multi-channel applications. The package consist of (1) a Numpy implementation which can easily be integrated into a custom Python toolchain, and (2) a TensorFlow implementation which allows integration into larger computational graphs and enables backpropagation through WPE to train more advanced front-ends. This package comprises of an iterative offline (batch) version, a block-online version, and a frame-online version which can be used in moderately low latency applications, e.g. digital speech assistants."}],"year":"2018","project":[{"_id":"52","name":"Computing Resources Provided by the Paderborn Center for Parallel Computing"}],"status":"public"}