{"id":"https://openalex.org/W2163751836","doi":"https://doi.org/10.21437/eurospeech.2001-75","title":"Robust digit recognition in noise: an evaluation using the AURORA corpus","display_name":"Robust digit recognition in noise: an evaluation using the AURORA corpus","publication_year":2001,"publication_date":"2001-09-03","ids":{"openalex":"https://openalex.org/W2163751836","doi":"https://doi.org/10.21437/eurospeech.2001-75","mag":"2163751836"},"language":"en","primary_location":{"id":"doi:10.21437/eurospeech.2001-75","is_oa":false,"landing_page_url":"https://doi.org/10.21437/eurospeech.2001-75","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"7th European Conference on Speech Communication and Technology (Eurospeech 2001)","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/A5084965575","display_name":"Umit Yapanel","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Umit Yapanel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057910370","display_name":"John H. L. Hansen","orcid":"https://orcid.org/0000-0003-1382-9929"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"John H. L. Hansen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072875068","display_name":"Ruhi Sarikaya","orcid":"https://orcid.org/0000-0003-2676-2831"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ruhi Sarikaya","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5000755345","display_name":"Bryan Pellom","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bryan Pellom","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"209","last_page":"212"},"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":0.9997000098228455,"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":0.9995999932289124,"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":0.7056546807289124},{"id":"https://openalex.org/keywords/numerical-digit","display_name":"Numerical digit","score":0.6860151886940002},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6538079977035522},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.625013530254364},{"id":"https://openalex.org/keywords/digit-recognition","display_name":"Digit recognition","score":0.5872935056686401},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39076778292655945},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.08515486121177673},{"id":"https://openalex.org/keywords/arithmetic","display_name":"Arithmetic","score":0.07923445105552673},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07471975684165955}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7056546807289124},{"id":"https://openalex.org/C94957134","wikidata":"https://www.wikidata.org/wiki/Q82990","display_name":"Numerical digit","level":2,"score":0.6860151886940002},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6538079977035522},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.625013530254364},{"id":"https://openalex.org/C2984784707","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Digit recognition","level":3,"score":0.5872935056686401},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39076778292655945},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.08515486121177673},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.07923445105552673},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07471975684165955},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.21437/eurospeech.2001-75","is_oa":false,"landing_page_url":"https://doi.org/10.21437/eurospeech.2001-75","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"7th European Conference on Speech Communication and Technology (Eurospeech 2001)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.6399999856948853,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W61569622","https://openalex.org/W1627054999","https://openalex.org/W1799381022","https://openalex.org/W1920183217","https://openalex.org/W2018228148","https://openalex.org/W2045036776","https://openalex.org/W2072328708","https://openalex.org/W2080921589","https://openalex.org/W2096503735","https://openalex.org/W2112163515","https://openalex.org/W2113911479","https://openalex.org/W2121973264","https://openalex.org/W2142193238"],"related_works":["https://openalex.org/W2911525106","https://openalex.org/W4322746633","https://openalex.org/W2736239746","https://openalex.org/W2169083538","https://openalex.org/W2397763568","https://openalex.org/W2365666152","https://openalex.org/W3154661292","https://openalex.org/W3037127226","https://openalex.org/W4367793605","https://openalex.org/W3208111892"],"abstract_inverted_index":{"In":[0,150],"this":[1],"paper,":[2],"a":[3,72,105],"variety":[4],"of":[5,74,115],"techniques":[6,158],"for":[7],"robust":[8],"digit":[9],"recognition":[10,33,66],"in":[11,27,90,95,100],"noise":[12,38,81],"are":[13,58],"considered":[14,71],"using":[15,109],"the":[16,42,53,140,147,151,168],"AURORA":[17],"2.0":[18],"corpus.":[19],"Current":[20],"recognizers":[21],"perform":[22],"as":[23,25,86],"well":[24],"humans":[26],"small":[28],"vocabulary":[29],"tasks":[30],"but":[31,127],"computer":[32],"performance":[34,46,125],"degrades":[35],"substantially":[36],"when":[37],"is":[39,47,186],"introduced":[40],"into":[41],"speech,":[43],"while":[44],"human":[45],"much":[48,164,187],"less":[49],"sensitive.":[50],"To":[51],"make":[52],"recognizer":[54],"robust,":[55],"several":[56],"methodologies":[57],"employed.":[59],"These":[60],"include,":[61],"feature":[62,106],"processing,":[63],"enhancement":[64,123],"before":[65],"and":[67,76,162],"model":[68,156,192],"adaptation.":[69,193],"We":[70],"number":[73],"processing":[75,107],"adaptation":[77,157,174],"scenarios":[78],"depending":[79],"on":[80],"type.":[82],"The":[83],"best":[84,148],"performance,":[85],"expected,":[87],"was":[88],"obtained":[89,133],"matched":[91,135,169],"training":[92],"conditions":[93],"which":[94,159,183],"general":[96],"has":[97],"limited":[98],"applicability":[99],"real":[101],"world":[102],"problems.":[103],"As":[104],"step,":[108,153],"RCCs":[110],"(Root":[111],"Cepstrum":[112],"Coeff.)":[113],"instead":[114],"MFCCs":[116],"gave":[117,163],"substantial":[118],"improvement.":[119],"MFCC":[120,173],"with":[121,134,142,180],"front-end":[122,181],"increased":[124],"considerably,":[126],"results":[128,166],"were":[129],"far":[130],"from":[131],"that":[132],"training.":[136],"When":[137],"we":[138,145,154,184],"combine":[139],"RCC":[141,178],"enhancement,":[143,182],"however,":[144],"get":[146],"results.":[149],"next":[152],"employed":[155],"outperformed":[160],"MFCC+enhancement":[161],"closer":[165],"to":[167],"condition":[170],"limits.":[171],"However,":[172],"could":[175],"not":[176],"outperform":[177],"parameterization":[179],"show":[185],"more":[188],"computationally":[189],"efficient":[190],"than":[191]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
