{"id":"https://openalex.org/W3094806148","doi":"https://doi.org/10.21437/interspeech.2020-1706","title":"X-TaSNet: Robust and Accurate Time-Domain Speaker Extraction Network","display_name":"X-TaSNet: Robust and Accurate Time-Domain Speaker Extraction Network","publication_year":2020,"publication_date":"2020-10-25","ids":{"openalex":"https://openalex.org/W3094806148","doi":"https://doi.org/10.21437/interspeech.2020-1706","mag":"3094806148"},"language":"en","primary_location":{"id":"doi:10.21437/interspeech.2020-1706","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2020-1706","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2020","raw_type":"proceedings-article"},"type":"article","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/A5030460543","display_name":"Zining Zhang","orcid":"https://orcid.org/0000-0002-7992-426X"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Zining Zhang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039946576","display_name":"Bingsheng He","orcid":"https://orcid.org/0000-0001-8618-4581"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bingsheng He","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100633295","display_name":"Zhenjie Zhang","orcid":"https://orcid.org/0000-0003-2053-3771"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhenjie Zhang","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5030460543"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.7276,"has_fulltext":false,"cited_by_count":31,"citation_normalized_percentile":{"value":0.91198157,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9998999834060669,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9991000294685364,"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/T11309","display_name":"Music and Audio Processing","score":0.9979000091552734,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7520504593849182},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5354381203651428},{"id":"https://openalex.org/keywords/time-domain","display_name":"Time domain","score":0.49913668632507324},{"id":"https://openalex.org/keywords/extraction","display_name":"Extraction (chemistry)","score":0.47314608097076416},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4615483582019806},{"id":"https://openalex.org/keywords/speaker-verification","display_name":"Speaker verification","score":0.46077531576156616},{"id":"https://openalex.org/keywords/speaker-recognition","display_name":"Speaker recognition","score":0.44409456849098206},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32722729444503784},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11593422293663025},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.08091318607330322}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7520504593849182},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5354381203651428},{"id":"https://openalex.org/C103824480","wikidata":"https://www.wikidata.org/wiki/Q185889","display_name":"Time domain","level":2,"score":0.49913668632507324},{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.47314608097076416},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4615483582019806},{"id":"https://openalex.org/C2982762665","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker verification","level":3,"score":0.46077531576156616},{"id":"https://openalex.org/C133892786","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker recognition","level":2,"score":0.44409456849098206},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32722729444503784},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11593422293663025},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.08091318607330322},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.21437/interspeech.2020-1706","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2020-1706","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2020","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.4699999988079071,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2150532155","https://openalex.org/W2253551762","https://openalex.org/W1585307611","https://openalex.org/W2937813194","https://openalex.org/W1516392727","https://openalex.org/W2140022733","https://openalex.org/W3048612421","https://openalex.org/W1992933175","https://openalex.org/W4246918790","https://openalex.org/W1986964660"],"abstract_inverted_index":{"Extracting":[0],"the":[1,16,47,69,73,78,123,129,138,150,153,157,163,178],"speech":[2,14,26,32,101,131,140],"of":[3,30,68,75,80,137,152,159,195],"a":[4,12,20,98,112],"target":[5,17,63,179],"speaker":[6,160,180,196],"from":[7,15],"mixed":[8],"audios,":[9],"based":[10],"on":[11,72],"reference":[13],"speaker,":[18],"is":[19,181],"challenging":[21],"yet":[22],"powerful":[23],"technology":[24],"in":[25,162,174],"processing.":[27],"Recent":[28],"studies":[29],"speaker-independent":[31],"separation,":[33],"such":[34,168],"as":[35],"TasNet,":[36],"have":[37],"shown":[38],"promising":[39],"results":[40,154,184],"by":[41,96,155],"applying":[42],"deep":[43],"neural":[44,52],"networks":[45],"over":[46,142],"time-domain":[48],"waveform.":[49],"Such":[50],"separation":[51],"network":[53],"does":[54],"not":[55],"directly":[56],"generate":[57],"reliable":[58],"and":[59,77,115,135],"accurate":[60],"output":[61,139,164],"when":[62,82,177],"speakers":[64,76],"are":[65],"specified,":[66],"because":[67],"necessary":[70],"prior":[71],"number":[74],"lack":[79],"robustness":[81,124],"dealing":[83],"with":[84,86],"audios":[85,173],"absent":[87],"speakers.":[88],"In":[89],"this":[90],"paper,":[91],"we":[92],"break":[93],"these":[94],"limitations":[95],"introducing":[97],"new":[99,109],"speaker-aware":[100],"masking":[102],"method,":[103],"called":[104],"X-TaSNet.":[105],"Our":[106],"proposal":[107],"adopts":[108],"strategies,":[110],"including":[111],"distortion-based":[113],"loss":[114],"corresponding":[116],"alternating":[117],"training":[118],"scheme,":[119],"to":[120,166],"better":[121],"address":[122],"issue.":[125],"X-TaSNet":[126,147,186],"significantly":[127],"enhances":[128],"extracted":[130],"quality,":[132],"doubling":[133],"SDRi":[134],"SI-SNRi":[136],"audio":[141,165],"state-of-the-art":[143],"voice":[144],"filtering":[145],"approach.":[146],"also":[148],"improves":[149],"reliability":[151],"improving":[156],"accuracy":[158],"identity":[161],"95.4%,":[167],"that":[169],"it":[170],"returns":[171],"silent":[172],"most":[175],"cases":[176],"absent.":[182],"These":[183],"demonstrate":[185],"moves":[187],"one":[188],"solid":[189],"step":[190],"towards":[191],"more":[192],"practical":[193],"applications":[194],"extraction":[197],"technology.":[198]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}