{"id":"https://openalex.org/W2009934439","doi":"https://doi.org/10.1109/taslp.2014.2318514","title":"Memory-Enhanced Neural Networks and NMF for Robust ASR","display_name":"Memory-Enhanced Neural Networks and NMF for Robust ASR","publication_year":2014,"publication_date":"2014-04-18","ids":{"openalex":"https://openalex.org/W2009934439","doi":"https://doi.org/10.1109/taslp.2014.2318514","mag":"2009934439"},"language":"en","primary_location":{"id":"doi:10.1109/taslp.2014.2318514","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taslp.2014.2318514","pdf_url":null,"source":{"id":"https://openalex.org/S4210169297","display_name":"IEEE/ACM Transactions on Audio Speech and Language Processing","issn_l":"2329-9290","issn":["2329-9290","2329-9304"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/ACM Transactions on Audio, Speech, and Language Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://opus.bibliothek.uni-augsburg.de/opus4/files/72569/72569.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5030512300","display_name":"J\u00fcrgen T. Geiger","orcid":null},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jurgen T. Geiger","raw_affiliation_strings":["Institute for Human-Machine Communication, Technische Universit\u00e4t M\u00fcnchen, Munich, Germany","Institute for Human\u2013Machine Communication, Technische Universit\u00e4t M\u00fcnchen, Munich, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Human-Machine Communication, Technische Universit\u00e4t M\u00fcnchen, Munich, Germany","institution_ids":["https://openalex.org/I62916508"]},{"raw_affiliation_string":"Institute for Human\u2013Machine Communication, Technische Universit\u00e4t M\u00fcnchen, Munich, Germany","institution_ids":["https://openalex.org/I62916508"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016747567","display_name":"Felix Weninger","orcid":null},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Felix Weninger","raw_affiliation_strings":["Institute for Human-Machine Communication, Technische Universit\u00e4t M\u00fcnchen, Munich, Germany","Institute for Human\u2013Machine Communication, Technische Universit\u00e4t M\u00fcnchen, Munich, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Human-Machine Communication, Technische Universit\u00e4t M\u00fcnchen, Munich, Germany","institution_ids":["https://openalex.org/I62916508"]},{"raw_affiliation_string":"Institute for Human\u2013Machine Communication, Technische Universit\u00e4t M\u00fcnchen, Munich, Germany","institution_ids":["https://openalex.org/I62916508"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109012430","display_name":"Jort F. Gemmeke","orcid":null},"institutions":[{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Jort F. Gemmeke","raw_affiliation_strings":["Department ESAT, KU Leuven, Belgium","Department ESAT, KU Leuven, Leuven, Belgium#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department ESAT, KU Leuven, Belgium","institution_ids":["https://openalex.org/I99464096"]},{"raw_affiliation_string":"Department ESAT, KU Leuven, Leuven, Belgium#TAB#","institution_ids":["https://openalex.org/I99464096"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068023895","display_name":"Martin W\u00f6llmer","orcid":null},"institutions":[{"id":"https://openalex.org/I4210156768","display_name":"BMW Group (Germany)","ror":"https://ror.org/044kkbh92","country_code":"DE","type":"company","lineage":["https://openalex.org/I4210156768"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Martin Wollmer","raw_affiliation_strings":["BMW Group, Munich, Germany","BMW Group; Munich Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"BMW Group, Munich, Germany","institution_ids":["https://openalex.org/I4210156768"]},{"raw_affiliation_string":"BMW Group; Munich Germany","institution_ids":["https://openalex.org/I4210156768"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043060302","display_name":"Bj\u00f6rn W. Schuller","orcid":"https://orcid.org/0000-0002-6478-8699"},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Bjorn Schuller","raw_affiliation_strings":["Institute for Human-Machine Communication, Technische Universit\u00e4t M\u00fcnchen, Munich, Germany","Institute for Human-Machine Communication, Technische Universit\u00e4t M\u00fcnchen, Munich, Germany and Department of Computing, Imperial College London, London, UK#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Human-Machine Communication, Technische Universit\u00e4t M\u00fcnchen, Munich, Germany","institution_ids":["https://openalex.org/I62916508"]},{"raw_affiliation_string":"Institute for Human-Machine Communication, Technische Universit\u00e4t M\u00fcnchen, Munich, Germany and Department of Computing, Imperial College London, London, UK#TAB#","institution_ids":["https://openalex.org/I62916508"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039092855","display_name":"Gerhard Rigoll","orcid":"https://orcid.org/0000-0003-1096-1596"},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Gerhard Rigoll","raw_affiliation_strings":["Institute for Human-Machine Communication, Technische Universit\u00e4t M\u00fcnchen, Munich, Germany","Institute for Human\u2013Machine Communication, Technische Universit\u00e4t M\u00fcnchen, Munich, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Human-Machine Communication, Technische Universit\u00e4t M\u00fcnchen, Munich, Germany","institution_ids":["https://openalex.org/I62916508"]},{"raw_affiliation_string":"Institute for Human\u2013Machine Communication, Technische Universit\u00e4t M\u00fcnchen, Munich, Germany","institution_ids":["https://openalex.org/I62916508"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.5033,"has_fulltext":true,"cited_by_count":31,"citation_normalized_percentile":{"value":0.96435863,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"22","issue":"6","first_page":"1037","last_page":"1046"},"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":0.9995999932289124,"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":0.9944000244140625,"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":0.7855310440063477},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7590357065200806},{"id":"https://openalex.org/keywords/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.7507710456848145},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7139548063278198},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.7023217678070068},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.6551416516304016},{"id":"https://openalex.org/keywords/reverberation","display_name":"Reverberation","score":0.6095371246337891},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.5589552521705627},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5158495306968689},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5124049782752991},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4656307101249695},{"id":"https://openalex.org/keywords/speech-enhancement","display_name":"Speech enhancement","score":0.45757102966308594},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.2705461382865906},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.13505738973617554}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7855310440063477},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7590357065200806},{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.7507710456848145},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7139548063278198},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.7023217678070068},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.6551416516304016},{"id":"https://openalex.org/C95851461","wikidata":"https://www.wikidata.org/wiki/Q468809","display_name":"Reverberation","level":2,"score":0.6095371246337891},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.5589552521705627},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5158495306968689},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5124049782752991},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4656307101249695},{"id":"https://openalex.org/C2776182073","wikidata":"https://www.wikidata.org/wiki/Q7575395","display_name":"Speech enhancement","level":3,"score":0.45757102966308594},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.2705461382865906},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.13505738973617554},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","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/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/taslp.2014.2318514","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taslp.2014.2318514","pdf_url":null,"source":{"id":"https://openalex.org/S4210169297","display_name":"IEEE/ACM Transactions on Audio Speech and Language Processing","issn_l":"2329-9290","issn":["2329-9290","2329-9304"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/ACM Transactions on Audio, Speech, and Language Processing","raw_type":"journal-article"},{"id":"pmh:oai:uni-augsburg.opus-bayern.de:72569","is_oa":true,"landing_page_url":"https://nbn-resolving.org/urn:nbn:de:bvb:384-opus4-725698","pdf_url":"https://opus.bibliothek.uni-augsburg.de/opus4/files/72569/72569.pdf","source":{"id":"https://openalex.org/S4306400930","display_name":"OPUS (Augsburg University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I119916105","host_organization_name":"Augsburg University","host_organization_lineage":["https://openalex.org/I119916105"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.434.6042","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.434.6042","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.mmk.ei.tum.de/publ//pdf/14/14gei3.pdf","raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:uni-augsburg.opus-bayern.de:72569","is_oa":true,"landing_page_url":"https://nbn-resolving.org/urn:nbn:de:bvb:384-opus4-725698","pdf_url":"https://opus.bibliothek.uni-augsburg.de/opus4/files/72569/72569.pdf","source":{"id":"https://openalex.org/S4306400930","display_name":"OPUS (Augsburg University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I119916105","host_organization_name":"Augsburg University","host_organization_lineage":["https://openalex.org/I119916105"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.6700000166893005,"display_name":"Reduced inequalities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"},{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"},{"id":"https://openalex.org/F4320321114","display_name":"Bundesministerium f\u00fcr Bildung und Forschung","ror":"https://ror.org/04pz7b180"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2009934439.pdf","grobid_xml":"https://content.openalex.org/works/W2009934439.grobid-xml"},"referenced_works_count":52,"referenced_works":["https://openalex.org/W24721013","https://openalex.org/W994258480","https://openalex.org/W1524333225","https://openalex.org/W1581242383","https://openalex.org/W1899504021","https://openalex.org/W1958840057","https://openalex.org/W1993882792","https://openalex.org/W2002342963","https://openalex.org/W2005638789","https://openalex.org/W2010023285","https://openalex.org/W2023952145","https://openalex.org/W2038720982","https://openalex.org/W2062164080","https://openalex.org/W2063224314","https://openalex.org/W2064675550","https://openalex.org/W2068144845","https://openalex.org/W2070707809","https://openalex.org/W2075888317","https://openalex.org/W2079735306","https://openalex.org/W2100643000","https://openalex.org/W2101045344","https://openalex.org/W2104448323","https://openalex.org/W2114217273","https://openalex.org/W2115730999","https://openalex.org/W2117172387","https://openalex.org/W2124149378","https://openalex.org/W2125234026","https://openalex.org/W2131774270","https://openalex.org/W2133676762","https://openalex.org/W2141520175","https://openalex.org/W2143612262","https://openalex.org/W2144499799","https://openalex.org/W2147706354","https://openalex.org/W2152051032","https://openalex.org/W2158336491","https://openalex.org/W2160815625","https://openalex.org/W2161459043","https://openalex.org/W2288838913","https://openalex.org/W2293661474","https://openalex.org/W2328757576","https://openalex.org/W2334833135","https://openalex.org/W2394967684","https://openalex.org/W2406070024","https://openalex.org/W2407887291","https://openalex.org/W2490695385","https://openalex.org/W6625990923","https://openalex.org/W6631362777","https://openalex.org/W6641001895","https://openalex.org/W6675701829","https://openalex.org/W6696302077","https://openalex.org/W6702079475","https://openalex.org/W6711908631"],"related_works":["https://openalex.org/W2919389044","https://openalex.org/W1966856063","https://openalex.org/W2889693761","https://openalex.org/W2020571614","https://openalex.org/W2890579888","https://openalex.org/W2777466939","https://openalex.org/W2900450731","https://openalex.org/W2890828644","https://openalex.org/W2401089611","https://openalex.org/W2032826752"],"abstract_inverted_index":{"In":[0,72,168],"this":[1,73],"article":[2],"we":[3,75,170],"address":[4],"the":[5,29,44,55,102,115,149,165,172,180,187,191,210,216],"problem":[6],"of":[7,31,46,145,154,174,190,215],"distant":[8],"speech":[9,177],"recognition":[10,231],"for":[11,176],"reverberant":[12],"noisy":[13],"environments.":[14],"Speech":[15,194],"enhancement":[16,178],"methods,":[17],"e.":[18],"g.,":[19],"using":[20,49],"non-negative":[21],"matrix":[22],"factorization":[23],"(NMF),":[24],"are":[25,40,131,184],"succesful":[26],"in":[27,92,101,164],"improving":[28,155],"robustness":[30,45,116],"ASR":[32],"systems.":[33],"Furthermore,":[34],"discriminative":[35],"training":[36],"and":[37,112,119,196,202],"feature":[38],"transformations":[39],"employed":[41],"to":[42,69,107,125,136],"increase":[43],"traditional":[47],"systems":[48],"Gaussian":[50],"mixture":[51],"models":[52,59],"(GMM).":[53],"On":[54],"other":[56],"hand,":[57],"acoustic":[58,141],"based":[60],"on":[61,179,186],"deep":[62,84],"neural":[63,90],"networks":[64,97],"(DNN)":[65],"were":[66],"recently":[67],"shown":[68],"outperform":[70],"GMMs.":[71],"work,":[74],"combine":[76],"a":[77,83,93,156,228],"state-of-the":[78],"art":[79],"GMM":[80,159],"system":[81,151],"with":[82],"Long":[85],"Short-Term":[86],"Memory":[87],"(LSTM)":[88],"recurrent":[89],"network":[91,122],"double-stream":[94],"architecture.":[95],"Such":[96],"use":[98],"memory":[99],"cells":[100],"hidden":[103],"units,":[104],"enabling":[105],"them":[106],"learn":[108],"long-range":[109],"temporal":[110],"context,":[111],"thus":[113],"increasing":[114],"against":[117],"noise":[118],"reverberation.":[120],"The":[121,224],"is":[123,144,152,162,219,233],"trained":[124],"predict":[126],"frame-wise":[127],"phoneme":[128],"estimates,":[129],"which":[130,161,199],"converted":[132],"into":[133],"observation":[134],"likelihoods":[135],"be":[137],"used":[138],"as":[139],"an":[140],"model.":[142],"It":[143],"particular":[146],"interest":[147],"whether":[148],"LSTM":[150],"capable":[153],"robust":[157],"state-of-the-art":[158,230],"system,":[160,232],"confirmed":[163],"experimental":[166],"results.":[167],"addition,":[169],"investigate":[171],"efficiency":[173],"NMF":[175],"front-end":[181],"side.":[182],"Experiments":[183],"conducted":[185],"medium-vocabulary":[188],"task":[189],"2nd":[192],"`CHiME'":[193],"Separation":[195],"Recognition":[197],"Challenge,":[198],"includes":[200],"reverberation":[201],"highly":[203],"variable":[204],"noise.":[205],"Experimental":[206],"results":[207],"show":[208],"that":[209],"average":[211],"word":[212],"error":[213],"rate":[214],"challenge":[217,226],"baseline":[218],"reduced":[220],"by":[221,235],"64%":[222],"relative.":[223,237],"best":[225],"entry,":[227],"noise-robust":[229],"outperformed":[234],"25%":[236]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":5},{"year":2015,"cited_by_count":6},{"year":2014,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}