[{"type":"conference","department":[{"_id":"54"}],"file":[{"date_created":"2023-05-16T08:37:31Z","creator":"frra","file_id":"44856","content_type":"application/pdf","file_name":"2106.05627.pdf","access_level":"open_access","file_size":295972,"relation":"main_file","date_updated":"2023-11-15T15:29:32Z"}],"date_created":"2023-05-15T07:59:33Z","abstract":[{"lang":"eng","text":"Unsupervised blind source separation methods do not require a training phase\r\nand thus cannot suffer from a train-test mismatch, which is a common concern in\r\nneural network based source separation. The unsupervised techniques can be\r\ncategorized in two classes, those building upon the sparsity of speech in the\r\nShort-Time Fourier transform domain and those exploiting non-Gaussianity or\r\nnon-stationarity of the source signals. In this contribution, spatial mixture\r\nmodels which fall in the first category and independent vector analysis (IVA)\r\nas a representative of the second category are compared w.r.t. their separation\r\nperformance and the performance of a downstream speech recognizer on a\r\nreverberant dataset of reasonable size. Furthermore, we introduce a serial\r\nconcatenation of the two, where the result of the mixture model serves as\r\ninitialization of IVA, which achieves significantly better WER performance than\r\neach algorithm individually and even approaches the performance of a much more\r\ncomplex neural network based technique."}],"publication":"ITG Conference on Speech Communication","main_file_link":[{"open_access":"1","url":"https://arxiv.org/pdf/2106.05627.pdf"}],"language":[{"iso":"eng"}],"date_updated":"2023-11-15T15:29:32Z","year":"2021","title":"A Comparison and Combination of Unsupervised Blind Source Separation  Techniques","author":[{"full_name":"Boeddeker, Christoph","first_name":"Christoph","last_name":"Boeddeker","id":"40767"},{"first_name":"Frederik","last_name":"Rautenberg","full_name":"Rautenberg, Frederik","id":"72602"},{"full_name":"Haeb-Umbach, Reinhold","first_name":"Reinhold","last_name":"Haeb-Umbach","id":"242"}],"oa":"1","external_id":{"arxiv":["2106.05627"]},"file_date_updated":"2023-11-15T15:29:32Z","citation":{"short":"C. Boeddeker, F. Rautenberg, R. Haeb-Umbach, in: ITG Conference on Speech Communication, 2021.","ama":"Boeddeker C, Rautenberg F, Haeb-Umbach R. A Comparison and Combination of Unsupervised Blind Source Separation  Techniques. In: <i>ITG Conference on Speech Communication</i>. ; 2021.","chicago":"Boeddeker, Christoph, Frederik Rautenberg, and Reinhold Haeb-Umbach. “A Comparison and Combination of Unsupervised Blind Source Separation  Techniques.” In <i>ITG Conference on Speech Communication</i>, 2021.","bibtex":"@inproceedings{Boeddeker_Rautenberg_Haeb-Umbach_2021, title={A Comparison and Combination of Unsupervised Blind Source Separation  Techniques}, booktitle={ITG Conference on Speech Communication}, author={Boeddeker, Christoph and Rautenberg, Frederik and Haeb-Umbach, Reinhold}, year={2021} }","mla":"Boeddeker, Christoph, et al. “A Comparison and Combination of Unsupervised Blind Source Separation  Techniques.” <i>ITG Conference on Speech Communication</i>, 2021.","apa":"Boeddeker, C., Rautenberg, F., &#38; Haeb-Umbach, R. (2021). A Comparison and Combination of Unsupervised Blind Source Separation  Techniques. <i>ITG Conference on Speech Communication</i>. ITG Conference on Speech Communication, Kiel.","ieee":"C. Boeddeker, F. Rautenberg, and R. Haeb-Umbach, “A Comparison and Combination of Unsupervised Blind Source Separation  Techniques,” presented at the ITG Conference on Speech Communication, Kiel, 2021."},"user_id":"40767","ddc":["000"],"_id":"44843","has_accepted_license":"1","status":"public","conference":{"name":"ITG Conference on Speech Communication","location":"Kiel"}}]