{"id":"https://openalex.org/W4408354347","doi":"https://doi.org/10.1109/icassp49660.2025.10888872","title":"Speech Separation for Low-Resource Languages","display_name":"Speech Separation for Low-Resource Languages","publication_year":2025,"publication_date":"2025-03-12","ids":{"openalex":"https://openalex.org/W4408354347","doi":"https://doi.org/10.1109/icassp49660.2025.10888872"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49660.2025.10888872","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10888872","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5027146195","display_name":"Marvin Borsdorf","orcid":"https://orcid.org/0000-0003-1769-1621"},"institutions":[{"id":"https://openalex.org/I180437899","display_name":"University of Bremen","ror":"https://ror.org/04ers2y35","country_code":"DE","type":"education","lineage":["https://openalex.org/I180437899"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Marvin Borsdorf","raw_affiliation_strings":["University of Bremen,Machine Listening Lab,Bremen,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Bremen,Machine Listening Lab,Bremen,Germany","institution_ids":["https://openalex.org/I180437899"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060530570","display_name":"Zexu Pan","orcid":"https://orcid.org/0000-0002-8106-1176"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zexu Pan","raw_affiliation_strings":["Alibaba Group,Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Alibaba Group,Singapore","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106912518","display_name":"Pascal Himmelmann","orcid":null},"institutions":[{"id":"https://openalex.org/I120691247","display_name":"FernUniversit\u00e4t in Hagen","ror":"https://ror.org/04tkkr536","country_code":"DE","type":"education","lineage":["https://openalex.org/I120691247"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Pascal Himmelmann","raw_affiliation_strings":["FernUniversit&#x00E4;t in Hagen,Department of Mathematics and Computer Science,Hagen,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"FernUniversit&#x00E4;t in Hagen,Department of Mathematics and Computer Science,Hagen,Germany","institution_ids":["https://openalex.org/I120691247"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032690182","display_name":"Haizhou Li","orcid":"https://orcid.org/0000-0001-9158-9401"},"institutions":[{"id":"https://openalex.org/I4210099586","display_name":"Shenzhen Research Institute of Big Data","ror":"https://ror.org/00z1gwf89","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210099586"]},{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haizhou Li","raw_affiliation_strings":["The Chinese University of Hong Kong,School of Data Science, Shenzhen Research Institute of Big Data,Shenzhen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong,School of Data Science, Shenzhen Research Institute of Big Data,Shenzhen,China","institution_ids":["https://openalex.org/I4210116924","https://openalex.org/I4210099586"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058049725","display_name":"Tanja Schultz","orcid":"https://orcid.org/0000-0002-9809-7028"},"institutions":[{"id":"https://openalex.org/I180437899","display_name":"University of Bremen","ror":"https://ror.org/04ers2y35","country_code":"DE","type":"education","lineage":["https://openalex.org/I180437899"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Tanja Schultz","raw_affiliation_strings":["University of Bremen,Cognitive Systems Lab,Bremen,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Bremen,Cognitive Systems Lab,Bremen,Germany","institution_ids":["https://openalex.org/I180437899"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9668999910354614,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10575","display_name":"Wireless Communication Networks Research","score":0.9151999950408936,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7026050090789795},{"id":"https://openalex.org/keywords/separation","display_name":"Separation (statistics)","score":0.5198579430580139},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4117487370967865},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.376796692609787},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3248981535434723},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.09640741348266602}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7026050090789795},{"id":"https://openalex.org/C2776061190","wikidata":"https://www.wikidata.org/wiki/Q7451805","display_name":"Separation (statistics)","level":2,"score":0.5198579430580139},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4117487370967865},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.376796692609787},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3248981535434723},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.09640741348266602}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49660.2025.10888872","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10888872","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.5600000023841858}],"awards":[],"funders":[{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W66627554","https://openalex.org/W1991139021","https://openalex.org/W2033436836","https://openalex.org/W2084534958","https://openalex.org/W2091746061","https://openalex.org/W2221409856","https://openalex.org/W2460742184","https://openalex.org/W2734774145","https://openalex.org/W2952218014","https://openalex.org/W2962715207","https://openalex.org/W2962866211","https://openalex.org/W2964058413","https://openalex.org/W2972461907","https://openalex.org/W2972541922","https://openalex.org/W3015191643","https://openalex.org/W3015199127","https://openalex.org/W3016232124","https://openalex.org/W3024869864","https://openalex.org/W3095717210","https://openalex.org/W3096893582","https://openalex.org/W3139878283","https://openalex.org/W3163652268","https://openalex.org/W3167533889","https://openalex.org/W3185109982","https://openalex.org/W3197657464","https://openalex.org/W3198429080","https://openalex.org/W3201729870","https://openalex.org/W4210710538","https://openalex.org/W4220805458","https://openalex.org/W4224932525","https://openalex.org/W4226189894","https://openalex.org/W4296069279","https://openalex.org/W4312768311","https://openalex.org/W4367597591","https://openalex.org/W4392903251","https://openalex.org/W4402112059","https://openalex.org/W4402112268","https://openalex.org/W6631190155","https://openalex.org/W6739901393","https://openalex.org/W6777776875","https://openalex.org/W6789284391"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2071676784","https://openalex.org/W2376932109","https://openalex.org/W3204019825"],"abstract_inverted_index":{"Speech":[0],"separation":[1,41,67,75],"aims":[2],"to":[3,14,79,86,109,141],"equip":[4],"machines":[5],"with":[6],"the":[7,27,37,48,61,77,88,96,120,138],"human":[8],"ability":[9],"of":[10,39,50,91],"selective":[11],"listening,":[12],"i.e.":[13],"focus":[15],"attention":[16],"on":[17,65,124],"specific":[18],"information":[19],"in":[20,30,137],"spoken":[21,29],"communication.":[22],"Studies":[23],"have":[24],"shown":[25],"that":[26,101,112,134],"language":[28],"a":[31,143],"cocktail":[32],"party":[33],"scenario":[34],"matters.":[35],"While":[36],"development":[38,139,148],"speech":[40,66],"models":[42,111],"can":[43,106],"leverage":[44],"extensive":[45],"databases,":[46],"for":[47,68,114],"majority":[49],"languages":[51,94,105,126],"only":[52],"very":[53,62],"limited":[54],"data":[55,89,102],"is":[56],"available.":[57],"This":[58],"work":[59,113],"presents":[60],"first":[63],"study":[64],"low-resource":[69,93,115],"languages.":[70,116],"We":[71,99,132],"choose":[72],"blind":[73],"source":[74],"as":[76],"task":[78],"be":[80,107],"studied":[81],"and":[82,122,130,147],"analyze":[83],"three":[84],"strategies":[85],"overcome":[87],"scarcity":[90],"two":[92],"from":[95,103],"GlobalPhoneMS2":[97],"database.":[98],"show":[100,133],"other":[104],"used":[108],"develop":[110],"Finetuning":[117],"additionally":[118],"boosts":[119],"performance,":[121],"training":[123],"multiple":[125],"increases":[127],"both":[128],"performance":[129,146],"robustness.":[131],"dynamic":[135],"mixing":[136],"helps":[140],"find":[142],"trade-off":[144],"between":[145],"time.":[149]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
