{"id":"https://openalex.org/W2711861986","doi":"https://doi.org/10.1109/icassp.2017.7953163","title":"Student-teacher network learning with enhanced features","display_name":"Student-teacher network learning with enhanced features","publication_year":2017,"publication_date":"2017-03-01","ids":{"openalex":"https://openalex.org/W2711861986","doi":"https://doi.org/10.1109/icassp.2017.7953163","mag":"2711861986"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2017.7953163","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2017.7953163","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 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/A5001291873","display_name":"Shinji Watanabe","orcid":"https://orcid.org/0000-0002-5970-8631"},"institutions":[{"id":"https://openalex.org/I4210159266","display_name":"Mitsubishi Electric (United States)","ror":"https://ror.org/053jnhe44","country_code":"US","type":"company","lineage":["https://openalex.org/I1306287861","https://openalex.org/I4210133125","https://openalex.org/I4210159266"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shinji Watanabe","raw_affiliation_strings":["Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA","institution_ids":["https://openalex.org/I4210159266"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087554069","display_name":"Takaaki Hori","orcid":"https://orcid.org/0000-0003-4560-8039"},"institutions":[{"id":"https://openalex.org/I4210159266","display_name":"Mitsubishi Electric (United States)","ror":"https://ror.org/053jnhe44","country_code":"US","type":"company","lineage":["https://openalex.org/I1306287861","https://openalex.org/I4210133125","https://openalex.org/I4210159266"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Takaaki Hori","raw_affiliation_strings":["Mitsubishi Electric Research Laboratories (MERL), Cambridge MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mitsubishi Electric Research Laboratories (MERL), Cambridge MA, USA","institution_ids":["https://openalex.org/I4210159266"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076453358","display_name":"Jonathan Le Roux","orcid":"https://orcid.org/0000-0002-3451-171X"},"institutions":[{"id":"https://openalex.org/I4210159266","display_name":"Mitsubishi Electric (United States)","ror":"https://ror.org/053jnhe44","country_code":"US","type":"company","lineage":["https://openalex.org/I1306287861","https://openalex.org/I4210133125","https://openalex.org/I4210159266"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jonathan Le Roux","raw_affiliation_strings":["Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA","institution_ids":["https://openalex.org/I4210159266"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112763337","display_name":"John R. Hershey","orcid":null},"institutions":[{"id":"https://openalex.org/I4210159266","display_name":"Mitsubishi Electric (United States)","ror":"https://ror.org/053jnhe44","country_code":"US","type":"company","lineage":["https://openalex.org/I1306287861","https://openalex.org/I4210133125","https://openalex.org/I4210159266"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"John R. Hershey","raw_affiliation_strings":["Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA","institution_ids":["https://openalex.org/I4210159266"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210159266"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":80,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"5275","last_page":"5279"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":1.0,"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":1.0,"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":0.9976999759674072,"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/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8269364237785339},{"id":"https://openalex.org/keywords/speech-enhancement","display_name":"Speech enhancement","score":0.6051978468894958},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5654740333557129},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.561447024345398},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.43794018030166626},{"id":"https://openalex.org/keywords/degradation","display_name":"Degradation (telecommunications)","score":0.4285944402217865},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4268991947174072},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.41882947087287903},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.322478711605072},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.10236310958862305}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8269364237785339},{"id":"https://openalex.org/C2776182073","wikidata":"https://www.wikidata.org/wiki/Q7575395","display_name":"Speech enhancement","level":3,"score":0.6051978468894958},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5654740333557129},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.561447024345398},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.43794018030166626},{"id":"https://openalex.org/C2779679103","wikidata":"https://www.wikidata.org/wiki/Q5251805","display_name":"Degradation (telecommunications)","level":2,"score":0.4285944402217865},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4268991947174072},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.41882947087287903},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.322478711605072},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.10236310958862305},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2017.7953163","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2017.7953163","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.7900000214576721}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W49348824","https://openalex.org/W1524333225","https://openalex.org/W1821462560","https://openalex.org/W1989314204","https://openalex.org/W2061074721","https://openalex.org/W2070707809","https://openalex.org/W2101045344","https://openalex.org/W2116490148","https://openalex.org/W2134797427","https://openalex.org/W2148613904","https://openalex.org/W2288645994","https://openalex.org/W2289394825","https://openalex.org/W2289731793","https://openalex.org/W2294370754","https://openalex.org/W2398042854","https://openalex.org/W2402040300","https://openalex.org/W2512865187","https://openalex.org/W2517616541","https://openalex.org/W2559260703","https://openalex.org/W4232280717","https://openalex.org/W6631362777","https://openalex.org/W6679909955","https://openalex.org/W6712847557"],"related_works":["https://openalex.org/W2534928293","https://openalex.org/W1630865680","https://openalex.org/W2150099345","https://openalex.org/W3004580327","https://openalex.org/W3012501961","https://openalex.org/W1490077415","https://openalex.org/W2160318243","https://openalex.org/W3034806817","https://openalex.org/W4293463510","https://openalex.org/W2401089611"],"abstract_inverted_index":{"Recent":[0],"advances":[1],"in":[2,21,77,90,174,195,201],"distant-talking":[3,46],"ASR":[4,18,47,186],"research":[5],"have":[6],"confirmed":[7],"that":[8,129],"speech":[9,26,30,130],"enhancement":[10,27,75,131],"is":[11,132],"an":[12,189],"essential":[13],"technique":[14],"for":[15,211],"improving":[16],"the":[17,22,53,61,78,91,117,122,136,151,165,179,196,202,212],"performance,":[19],"especially":[20],"multichannel":[23],"scenario.":[24],"However,":[25],"inevitably":[28],"distorts":[29],"signals,":[31],"which":[32,144],"can":[33],"cause":[34],"significant":[35,185],"degradation":[36],"when":[37],"enhanced":[38,62,88,96,172],"signals":[39,56,63],"are":[40,98],"used":[41,99],"as":[42,57,100,126,149],"training":[43,58,79],"data.":[44],"Thus,":[45],"systems":[48],"often":[49],"resort":[50],"to":[51,84,102,106,115,159],"using":[52,121,207],"original":[54,123],"noisy":[55,124],"data":[59],"and":[60,68,199],"only":[64],"at":[65],"test":[66],"time,":[67],"give":[69],"up":[70],"on":[71],"taking":[72],"advantage":[73],"of":[74,87,168,171,193],"techniques":[76],"stage.":[80],"This":[81,162],"paper":[82],"proposes":[83],"make":[85],"use":[86,170],"features":[89,97,125,173,210],"student-teacher":[92,142],"learning":[93],"paradigm.":[94],"The":[95],"input":[101],"a":[103,111,146,160],"teacher":[104,118,213],"network":[105,113,148,175],"obtain":[107],"soft":[108],"targets,":[109],"while":[110],"student":[112,137],"tries":[114],"mimic":[116],"network's":[119],"outputs":[120],"input,":[127],"so":[128],"implicitly":[133],"performed":[134],"within":[135],"network.":[138],"Compared":[139],"with":[140,178,188],"conventional":[141],"learning,":[143],"uses":[145,155],"better":[147,156],"teacher,":[150],"proposed":[152],"self-supervised":[153],"method":[154],"(enhanced)":[157],"inputs":[158],"teacher.":[161],"setup":[163],"matches":[164],"above":[166],"scenario":[167],"making":[169],"training.":[176],"Experiments":[177],"CHiME-4":[180],"challenge":[181],"real":[182],"dataset":[183],"show":[184],"improvements":[187],"error":[190],"reduction":[191],"rate":[192],"12%":[194],"single-channel":[197],"track":[198],"15%":[200],"2-channel":[203],"track,":[204],"respectively,":[205],"by":[206],"6-channel":[208],"beamformed":[209],"model.":[214]},"counts_by_year":[{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":17},{"year":2020,"cited_by_count":13},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":21},{"year":2017,"cited_by_count":5}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
