{"id":"https://openalex.org/W2099480894","doi":"https://doi.org/10.21437/eurospeech.2001-81","title":"Feature extraction and model-based noise compensation for noisy speech recognition evaluated on AURORA 2 task","display_name":"Feature extraction and model-based noise compensation for noisy speech recognition evaluated on AURORA 2 task","publication_year":2001,"publication_date":"2001-09-03","ids":{"openalex":"https://openalex.org/W2099480894","doi":"https://doi.org/10.21437/eurospeech.2001-81","mag":"2099480894"},"language":"en","primary_location":{"id":"doi:10.21437/eurospeech.2001-81","is_oa":false,"landing_page_url":"https://doi.org/10.21437/eurospeech.2001-81","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":"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/A5103119755","display_name":"Kaisheng Yao","orcid":"https://orcid.org/0000-0002-8949-9367"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Kaisheng Yao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056129529","display_name":"Jingdong Chen","orcid":"https://orcid.org/0000-0003-0083-9247"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jingdong Chen","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046089538","display_name":"Kuldip K. Paliwal","orcid":"https://orcid.org/0000-0002-3553-3662"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kuldip K. Paliwal","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5020994673","display_name":"Satoshi Nakamura","orcid":"https://orcid.org/0000-0001-6956-3803"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Satoshi Nakamura","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5103119755"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3117,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.62404837,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"233","last_page":"236"},"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":0.9994999766349792,"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":0.9993000030517578,"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/robustness","display_name":"Robustness (evolution)","score":0.7339922189712524},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7134230136871338},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6157132983207703},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5862894654273987},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5743880271911621},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5597126483917236},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5325635671615601},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.5252763032913208},{"id":"https://openalex.org/keywords/speech-enhancement","display_name":"Speech enhancement","score":0.4249507188796997},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.23164665699005127}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7339922189712524},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7134230136871338},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6157132983207703},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5862894654273987},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5743880271911621},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5597126483917236},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5325635671615601},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.5252763032913208},{"id":"https://openalex.org/C2776182073","wikidata":"https://www.wikidata.org/wiki/Q7575395","display_name":"Speech enhancement","level":3,"score":0.4249507188796997},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.23164665699005127},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.21437/eurospeech.2001-81","is_oa":false,"landing_page_url":"https://doi.org/10.21437/eurospeech.2001-81","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"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.59.1334","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.59.1334","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://maxwell.me.gu.edu.au/spl/publications/papers/euro01_yao_aurora.pdf","raw_type":"text"},{"id":"pmh:oai:research-repository.griffith.edu.au:10072/1259","is_oa":false,"landing_page_url":"http://hdl.handle.net/10072/1259","pdf_url":null,"source":{"id":"https://openalex.org/S4306402548","display_name":"Griffith Research Online (Griffith University, Queensland, Australia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I11701301","host_organization_name":"Griffith University","host_organization_lineage":["https://openalex.org/I11701301"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference output"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W2116763853","https://openalex.org/W2128653836","https://openalex.org/W2151484683","https://openalex.org/W2157702502"],"related_works":["https://openalex.org/W1996690921","https://openalex.org/W3096184950","https://openalex.org/W4231424160","https://openalex.org/W2275432853","https://openalex.org/W2002243964","https://openalex.org/W2022538999","https://openalex.org/W3090086172","https://openalex.org/W1955763106","https://openalex.org/W2025188156","https://openalex.org/W4375869276"],"abstract_inverted_index":{"We":[0,23,40],"have":[1,122],"evaluated":[2],"several":[3],"feature-based":[4,103],"and":[5,117],"a":[6,27,43,81,100],"model-based":[7,82,119],"method":[8,85,120],"for":[9,113],"robust":[10,36,44,57,63],"speech":[11],"recognition":[12],"in":[13,111],"noise.":[14,39,94],"The":[15],"evaluation":[16],"was":[17],"performed":[18],"on":[19,132],"Aurora":[20],"2":[21],"task.":[22],"show":[24,79],"that":[25,80],"after":[26],"subband":[28],"based":[29],"spectral":[30],"subtraction,":[31],"features":[32],"can":[33,86,105,121],"be":[34,87],"more":[35],"to":[37,58,64,68,89,93],"additive":[38,59],"also":[41,62],"report":[42],"feature":[45],"set":[46,75],"derived":[47],"from":[48],"differential":[49],"power":[50],"spectrum":[51,65],"(DPS),":[52],"which":[53],"is":[54,76],"not":[55],"only":[56],"noise,":[60],"but":[61],"colorization":[66],"due":[67],"channel":[69],"effects.":[70],"When":[71],"the":[72,96,102,118],"clean":[73,133],"training":[74,115,134],"available,":[77],"we":[78],"noise":[83],"compensation":[84],"effective":[88],"improve":[90],"system":[91],"robustness":[92],"Given":[95],"testing":[97],"sets,":[98],"as":[99],"whole,":[101],"methods":[104],"yield":[106],"about":[107,123],"22%":[108],"relative":[109,125],"improvement":[110,127],"accuracy":[112],"multi-condition":[114],"task,":[116],"63%":[124],"performance":[126],"when":[128],"systems":[129],"were":[130],"trained":[131],"set.":[135]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
