{"project":[{"name":"Computing Resources Provided by the Paderborn Center for Parallel Computing","_id":"52"}],"ddc":["000"],"abstract":[{"text":"We present a multi-channel database of overlapping speech for training, evaluation, and detailed analysis of source separation and extraction algorithms: SMS-WSJ -- Spatialized Multi-Speaker Wall Street Journal. It consists of artificially mixed speech taken from the WSJ database, but unlike earlier databases we consider all WSJ0+1 utterances and take care of strictly separating the speaker sets present in the training, validation and test sets. When spatializing the data we ensure a high degree of randomness w.r.t. room size, array center and rotation, as well as speaker position. Furthermore, this paper offers a critical assessment of recently proposed measures of source separation performance. Alongside the code to generate the database we provide a source separation baseline and a Kaldi recipe with competitive word error rates to provide common ground for evaluation.","lang":"eng"}],"author":[{"last_name":"Drude","first_name":"Lukas","full_name":"Drude, Lukas"},{"last_name":"Heitkaemper","id":"27643","first_name":"Jens","full_name":"Heitkaemper, Jens"},{"last_name":"Boeddeker","first_name":"Christoph","id":"40767","full_name":"Boeddeker, Christoph"},{"full_name":"Haeb-Umbach, Reinhold","first_name":"Reinhold","id":"242","last_name":"Haeb-Umbach"}],"citation":{"mla":"Drude, Lukas, et al. “SMS-WSJ: Database, Performance Measures, and Baseline Recipe for Multi-Channel Source Separation and Recognition.” <i>ArXiv E-Prints</i>, 2019.","apa":"Drude, L., Heitkaemper, J., Boeddeker, C., &#38; Haeb-Umbach, R. (2019). SMS-WSJ: Database, performance measures, and baseline recipe for multi-channel source separation and recognition. <i>ArXiv E-Prints</i>.","ama":"Drude L, Heitkaemper J, Boeddeker C, Haeb-Umbach R. SMS-WSJ: Database, performance measures, and baseline recipe for multi-channel source separation and recognition. <i>ArXiv e-prints</i>. 2019.","short":"L. Drude, J. Heitkaemper, C. Boeddeker, R. Haeb-Umbach, ArXiv E-Prints (2019).","ieee":"L. Drude, J. Heitkaemper, C. Boeddeker, and R. Haeb-Umbach, “SMS-WSJ: Database, performance measures, and baseline recipe for multi-channel source separation and recognition,” <i>ArXiv e-prints</i>, 2019.","bibtex":"@article{Drude_Heitkaemper_Boeddeker_Haeb-Umbach_2019, title={SMS-WSJ: Database, performance measures, and baseline recipe for multi-channel source separation and recognition}, journal={ArXiv e-prints}, author={Drude, Lukas and Heitkaemper, Jens and Boeddeker, Christoph and Haeb-Umbach, Reinhold}, year={2019} }","chicago":"Drude, Lukas, Jens Heitkaemper, Christoph Boeddeker, and Reinhold Haeb-Umbach. “SMS-WSJ: Database, Performance Measures, and Baseline Recipe for Multi-Channel Source Separation and Recognition.” <i>ArXiv E-Prints</i>, 2019."},"has_accepted_license":"1","file":[{"date_created":"2020-09-16T08:00:56Z","relation":"main_file","access_level":"open_access","creator":"huesera","content_type":"application/pdf","file_size":288594,"file_id":"19448","file_name":"ArXiv_2019_Drude.pdf","date_updated":"2020-12-11T12:22:31Z"}],"publication":"ArXiv e-prints","_id":"19446","status":"public","user_id":"40767","date_updated":"2022-01-06T06:54:04Z","type":"journal_article","language":[{"iso":"eng"}],"file_date_updated":"2020-12-11T12:22:31Z","year":"2019","date_created":"2020-09-16T07:59:46Z","title":"SMS-WSJ: Database, performance measures, and baseline recipe for multi-channel source separation and recognition","oa":"1","department":[{"_id":"54"}]}