{"id":"https://openalex.org/W27865004","doi":"https://doi.org/10.21437/interspeech.2010-482","title":"Improved spoken term detection by feature space pseudo-relevance feedback","display_name":"Improved spoken term detection by feature space pseudo-relevance feedback","publication_year":2010,"publication_date":"2010-09-26","ids":{"openalex":"https://openalex.org/W27865004","doi":"https://doi.org/10.21437/interspeech.2010-482","mag":"27865004"},"language":"en","primary_location":{"id":"doi:10.21437/interspeech.2010-482","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2010-482","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2010","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/A5087434278","display_name":"Chia-Ping Chen","orcid":"https://orcid.org/0000-0002-7022-3061"},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chia-ping Chen","raw_affiliation_strings":["National Taiwan University, Taipei, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Taiwan University, Taipei, Taiwan","institution_ids":["https://openalex.org/I16733864"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040508737","display_name":"Hung-yi Lee","orcid":"https://orcid.org/0000-0002-9654-5747"},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Hung-yi Lee","raw_affiliation_strings":["National Taiwan University, Taipei, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Taiwan University, Taipei, Taiwan","institution_ids":["https://openalex.org/I16733864"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087421101","display_name":"Ching-Feng Yeh","orcid":null},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Ching-feng Yeh","raw_affiliation_strings":["National Taiwan University > > > >  >  >"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Taiwan University > > > >  >  >","institution_ids":["https://openalex.org/I16733864"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044010123","display_name":"Lin-shan Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I84653119","display_name":"Academia Sinica","ror":"https://ror.org/05bxb3784","country_code":"TW","type":"facility","lineage":["https://openalex.org/I84653119"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Lin-shan Lee","raw_affiliation_strings":["Academia Sinica )"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Academia Sinica )","institution_ids":["https://openalex.org/I84653119"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.542,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.93619265,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1672","last_page":"1675"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"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"}},"topics":[{"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9980000257492065,"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/T12031","display_name":"Speech and dialogue systems","score":0.9965999722480774,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7609142661094666},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.7451278567314148},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.7445346117019653},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.7057256102561951},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6133184432983398},{"id":"https://openalex.org/keywords/mel-frequency-cepstrum","display_name":"Mel-frequency cepstrum","score":0.581051230430603},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.48866990208625793},{"id":"https://openalex.org/keywords/spoken-language","display_name":"Spoken language","score":0.46248894929885864},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4585362374782562},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.41343551874160767},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4021710753440857},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.3755883574485779},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33607012033462524},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.11989724636077881}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7609142661094666},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.7451278567314148},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.7445346117019653},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.7057256102561951},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6133184432983398},{"id":"https://openalex.org/C151989614","wikidata":"https://www.wikidata.org/wiki/Q440370","display_name":"Mel-frequency cepstrum","level":3,"score":0.581051230430603},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.48866990208625793},{"id":"https://openalex.org/C2776230583","wikidata":"https://www.wikidata.org/wiki/Q1322198","display_name":"Spoken language","level":2,"score":0.46248894929885864},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4585362374782562},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.41343551874160767},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4021710753440857},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3755883574485779},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33607012033462524},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.11989724636077881},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.21437/interspeech.2010-482","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2010-482","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2010","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"No poverty","score":0.41999998688697815,"id":"https://metadata.un.org/sdg/1"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W1578200545","https://openalex.org/W1984375608","https://openalex.org/W2063614293","https://openalex.org/W2075224964","https://openalex.org/W2101024576","https://openalex.org/W2110625382","https://openalex.org/W2114512077","https://openalex.org/W2116110832","https://openalex.org/W2171019095"],"related_works":["https://openalex.org/W2349769824","https://openalex.org/W2914532148","https://openalex.org/W2372625757","https://openalex.org/W4313178214","https://openalex.org/W3093766508","https://openalex.org/W4317383455","https://openalex.org/W2548511587","https://openalex.org/W2422472940","https://openalex.org/W2019475500","https://openalex.org/W2548162870"],"abstract_inverted_index":{"Abstract":[0],"In":[1,142,181,470,510],"this":[2,182,568,640],"paper,":[3,569],"we":[4,37,570],"propose":[5],"an":[6],"improved":[7],"approach":[8,637],"for":[9,64,543,576,610],"spokenterm":[10],"detection":[11,127,224,566,579],"using":[12],"pseudo-relevance":[13,121,559],"feedback.":[14],"To":[15],"remedy":[16],"theproblem":[17],"of":[18,54,69,133,185,212,232,266,286,309,386,456,467,518,523,558,587,648],"unmatched":[19],"acoustic":[20,29,109,190,203,214,274],"models":[21,204],"with":[22,45,549,628],"respect":[23],"to":[24,95,113,129,176,209,262,270,296,340,345,366,376,380,418,428,476,488,505,536,572,657],"spokenutterances":[25],"produced":[26],"under":[27,252],"different":[28,250,254,273],"conditions,":[30,256],"whichmay":[31],"give":[32],"relatively":[33,347],"poor":[34,223,348],"recognition":[35,221,349,607],"output,":[36,350],"integrate":[38],"therelevance":[39],"scores":[40,281,623],"derived":[41,49,290],"from":[42,50,73,291,354,551,600,625],"the":[43,46,51,74,85,96,108,114,136,140,148,165,170,177,186,189,196,202,210,213,237,244,279,284,287,298,310,313,342,346,355,364,381,390,397,422,436,478,482,507,516,524,547,591,604,611,614,618,621,626,630,634,645,658],"lattices":[44,159,173,316,609,627],"DTW":[47,60],"dis-tances":[48],"feature":[52,356],"space":[53,357],"MFCC":[55,596],"parametersor":[56],"phonetic":[57],"posteriorgrams.":[58],"These":[59],"distances":[61],"are":[62,151,246,294,486,528],"evalu-ated":[63],"a":[65,131,264,276,306,318,322,408,441,453],"carefully":[66],"selected":[67],"set":[68,265,517,664],"pseudo-relevant":[70],"utterances,which":[71],"obtained":[72,102,599],"\ufb01rst-pass":[75,86],"returned":[76,87,652],"list":[77,88,132,527,653],"given":[78],"by":[79,139,160,248,396,421,545,633],"thesearch":[80],"engine.":[81],"The":[82,636],"utterances":[83,150,241,619],"on":[84,563],"arethen":[89],"reranked":[90],"accordingly":[91],"and":[92,154,163,613],"\ufb01nally":[93],"shown":[94,581,643,656],"user.":[97,141,635],"Veryencouraging,":[98],"performance":[99],"improvements":[100],"were":[101,598],"in":[103,188,195,219,230,312,405,414,582,639,644],"thepreliminary":[104],"experiments,":[105],"especially":[106,200],"when":[107,201,278,325],"modelsare":[110],"poorly":[111],"matched":[112,208,269],"spoken":[115,118,134,145,149,233,240,564,577,593,602],"utterances.Index":[116],"Terms:":[117],"term":[119,126,137,146,234,289,383,394,455,466,565,578,594],"detection,":[120,147,235],"feed-back":[122],"1.":[123,584,650],"Introduction":[124],"Spoken":[125],"is":[128,227,258,302,317,328,373,474,502,513,590,642,654],"return":[130],"utterancescontaining":[135],"requested":[138],"many":[143,249,253,272,331,385,400],"approachesof":[144],"\ufb01rst":[152],"recog-nized":[153],"transformed":[155],"into":[156],"transcriptions":[157,171,292],"or":[158,172,315,321],"speechrecognition":[161],"technologies,":[162],"then":[164],"search":[166],"engine":[167,616],"looksthrough":[168],"all":[169,369,601],"very":[174,228,260,391],"similar":[175,535,574],"text-based":[178,359],"information":[179,352,360],"retrieval.":[180],"process":[183],"much":[184],"in-formation":[187],"signals":[191],"may":[192,403,424,450],"be":[193,419,429,451,541],"lost":[194],"stage":[197],"ofspeech":[198],"recognition,":[199],"usedare":[205],"not":[206,388,463,655],"well":[207,268],"characteristics":[211],"sig-nals,":[215],"which":[216],"naturally":[217],"results":[218],"degraded":[220],"accuracyand":[222],"performance.":[225],"This":[226],"common":[229],"thescenario":[231],"because":[236,384,399],"huge":[238],"quantitiesof":[239],"available":[242],"over":[243],"Internet":[245],"naturallyproduced":[247],"people":[251],"acous-tic":[255],"it":[257,301,372,433,461,473,512],"thus":[259],"dif\ufb01cult":[261,375],"train":[263],"acousticmodels":[267],"so":[271,532],"conditions.As":[275],"result,":[277],"relevance":[280,622],"such":[282],"as":[283,499,580],"posteriorprobabilities":[285],"query":[288,311,382,393,437,454,465,483,548,631],"orlattices":[293],"used":[295],"rank":[297],"retrieved":[299,490,525,615],"utterances,":[300],"hard":[303],"tojudge":[304],"whether":[305],"word":[307],"hypothesis":[308],"transcrip-tions":[314],"positive":[319],"target":[320],"false":[323],"alarm":[324],"therecognition":[326],"output":[327],"unreliable.":[329],"Although":[330],"ef\ufb01cient":[332],"ap-proaches":[333],"[1,":[334],"2,":[335],"3]":[336],"have":[337,425],"been":[338],"proposed":[339],"enhance":[341],"detectionperformance":[343],"due":[344],"thecompensative":[351],"straightly":[353],"isnecessary.In":[358],"retrieval,":[361],"even":[362,431,459],"if":[363,432,460],"texts":[365],"beretrieved":[367],"include":[368,389,435],"precise":[370],"words,":[371,472],"still":[374],"retrieveall":[377],"documents":[378,416,480,519,533,539],"relevant":[379,420,479,491,529],"themdo":[387],"short":[392],"entered":[395],"user.However,":[398],"related":[401],"terms":[402],"co-occur":[404],"manyrelated":[406],"documents,":[407],"document":[409,442,526],"containing":[410],"some":[411,415,489,493],"words":[412,444],"appear-ing":[413],"identi\ufb01ed":[417],"searchengine":[423],"high":[426],"probability":[427],"relevant,":[430],"doesnot":[434],"term.":[438],"For":[439],"example,":[440,544],"includingthe":[443],"\u201dGeorge":[445],"Bush\u201d,":[446],"\u201dUS\u201d,":[447],"\u201dMiddle":[448],"East\u201d":[449],"relevantto":[452],"\u201dWhite":[457,468],"House\u201d,":[458],"does":[462],"includethe":[464],"House\u201d.":[469],"other":[471],"possi-ble":[475],"retrieve":[477],"without":[481],"termsince":[484],"they":[485],"\u201dsimilar\u201d":[487],"documentsin":[492],"way.":[494],"Pseudo-relevance":[495],"feedback,":[496,501],"also":[497],"known":[498],"blindrelevance":[500],"one":[503],"way":[504],"realize":[506],"above":[508],"idea.":[509],"thisapproach,":[511],"assumed":[514],"that":[515],"appearing":[520],"onthe":[521],"top":[522],"(or":[530],"\u201dpseudo-relevant\u201d),":[531],"somehow":[534],"those":[537,552],"\u201dpseudo-relevant\u201d":[538,553],"can":[540],"retrieved,":[542],"expand-ing":[546],"keywords":[550],"doc-uments":[554],"[4].":[555],"Similar":[556],"idea":[557],"feedback":[560],"has":[561],"beenapplied":[562],"[5].In":[567],"try":[571],"perform":[573],"pseudo-relevancefeedback":[575],"Figure":[583,588,649],"Theupper":[585],"half":[586,647],"1":[589],"conventional":[592],"detec-tion.":[595],"features":[597],"utterancesin":[603],"archive,":[605],"speech":[606],"produces":[608],"ut-terances,":[612],"selects":[617],"basedon":[620],"evaluated":[624],"respectto":[629],"Qentered":[632],"proposedhere":[638],"paper":[641],"lower":[646],"The\ufb01rst-pass":[651],"user,":[659],"but":[660],"instead":[661],"a\u201dpseudo-relevant":[662],"utterance":[663],"X":[665]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2017,"cited_by_count":2},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":3},{"year":2012,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
