{"id":"https://openalex.org/W1992810169","doi":"https://doi.org/10.1109/icassp.2013.6639337","title":"A confidence-based approach for improving keyword hypothesis scores","display_name":"A confidence-based approach for improving keyword hypothesis scores","publication_year":2013,"publication_date":"2013-05-01","ids":{"openalex":"https://openalex.org/W1992810169","doi":"https://doi.org/10.1109/icassp.2013.6639337","mag":"1992810169"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2013.6639337","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2013.6639337","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Acoustics, Speech and Signal Processing","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/A5004439539","display_name":"M.S. Seigel","orcid":null},"institutions":[{"id":"https://openalex.org/I241749","display_name":"University of Cambridge","ror":"https://ror.org/013meh722","country_code":"GB","type":"education","lineage":["https://openalex.org/I241749"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"M.S. Seigel","raw_affiliation_strings":["Engineering Department, University of Cambridge, Cambridge, UK","Engineering Department, Cambridge University, Cambridge, UK,"],"affiliations":[{"raw_affiliation_string":"Engineering Department, University of Cambridge, Cambridge, UK","institution_ids":["https://openalex.org/I241749"]},{"raw_affiliation_string":"Engineering Department, Cambridge University, Cambridge, UK,","institution_ids":["https://openalex.org/I241749"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002191410","display_name":"Philip C. Woodland","orcid":"https://orcid.org/0000-0001-9069-0225"},"institutions":[{"id":"https://openalex.org/I241749","display_name":"University of Cambridge","ror":"https://ror.org/013meh722","country_code":"GB","type":"education","lineage":["https://openalex.org/I241749"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"P.C. Woodland","raw_affiliation_strings":["Engineering Department, University of Cambridge, Cambridge, UK","Engineering Department, Cambridge University, Cambridge, UK,"],"affiliations":[{"raw_affiliation_string":"Engineering Department, University of Cambridge, Cambridge, UK","institution_ids":["https://openalex.org/I241749"]},{"raw_affiliation_string":"Engineering Department, Cambridge University, Cambridge, UK,","institution_ids":["https://openalex.org/I241749"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050766679","display_name":"Mark Gales","orcid":"https://orcid.org/0000-0002-5311-8219"},"institutions":[{"id":"https://openalex.org/I241749","display_name":"University of Cambridge","ror":"https://ror.org/013meh722","country_code":"GB","type":"education","lineage":["https://openalex.org/I241749"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"M.J.F. Gales","raw_affiliation_strings":["Engineering Department, University of Cambridge, Cambridge, UK","Engineering Department, Cambridge University, Cambridge, UK,"],"affiliations":[{"raw_affiliation_string":"Engineering Department, University of Cambridge, Cambridge, UK","institution_ids":["https://openalex.org/I241749"]},{"raw_affiliation_string":"Engineering Department, Cambridge University, Cambridge, UK,","institution_ids":["https://openalex.org/I241749"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5004439539"],"corresponding_institution_ids":["https://openalex.org/I241749"],"apc_list":null,"apc_paid":null,"fwci":1.9152,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.85597985,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"8565","last_page":"8569"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music 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/T11309","display_name":"Music 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/T10860","display_name":"Speech and Audio Processing","score":0.9997000098228455,"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/discriminative-model","display_name":"Discriminative model","score":0.7975660562515259},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7232931852340698},{"id":"https://openalex.org/keywords/keyword-spotting","display_name":"Keyword spotting","score":0.6575804948806763},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.6206624507904053},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5040830373764038},{"id":"https://openalex.org/keywords/conditional-random-field","display_name":"Conditional random field","score":0.5009336471557617},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4979536533355713},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4935232400894165},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4771415889263153},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.4592864513397217},{"id":"https://openalex.org/keywords/confidence-interval","display_name":"Confidence interval","score":0.4385778307914734},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4289284646511078},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33469754457473755},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2387934923171997},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20166364312171936}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7975660562515259},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7232931852340698},{"id":"https://openalex.org/C2781213101","wikidata":"https://www.wikidata.org/wiki/Q6398558","display_name":"Keyword spotting","level":2,"score":0.6575804948806763},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.6206624507904053},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5040830373764038},{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.5009336471557617},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4979536533355713},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4935232400894165},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4771415889263153},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.4592864513397217},{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.4385778307914734},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4289284646511078},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33469754457473755},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2387934923171997},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20166364312171936},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2013.6639337","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2013.6639337","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Acoustics, Speech and Signal Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7300000190734863,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W23025778","https://openalex.org/W52233812","https://openalex.org/W56827455","https://openalex.org/W114193738","https://openalex.org/W131400518","https://openalex.org/W1508594724","https://openalex.org/W1528022942","https://openalex.org/W1586226485","https://openalex.org/W2012233267","https://openalex.org/W2015688877","https://openalex.org/W2051434435","https://openalex.org/W2102156675","https://openalex.org/W2106597349","https://openalex.org/W2110017413","https://openalex.org/W2110758086","https://openalex.org/W2129334286","https://openalex.org/W2139839651","https://openalex.org/W2147880316","https://openalex.org/W2164729205","https://openalex.org/W2274548782","https://openalex.org/W2280141299","https://openalex.org/W2397840928","https://openalex.org/W2404593419","https://openalex.org/W2789663420","https://openalex.org/W6600906190","https://openalex.org/W6602155318","https://openalex.org/W6604666349","https://openalex.org/W6630329364","https://openalex.org/W6631534535","https://openalex.org/W6675244807","https://openalex.org/W6679446661","https://openalex.org/W6680738810","https://openalex.org/W6682082992"],"related_works":["https://openalex.org/W2114097550","https://openalex.org/W4385352507","https://openalex.org/W2918559346","https://openalex.org/W4286904253","https://openalex.org/W84309476","https://openalex.org/W2386245264","https://openalex.org/W2388033618","https://openalex.org/W2163278254","https://openalex.org/W1574213390","https://openalex.org/W2886949521"],"abstract_inverted_index":{"The":[0,110],"task":[1],"in":[2,20,123,137,144],"keyword":[3],"spotting":[4],"(KWS)":[5],"is":[6,61,76,107],"to":[7,32,63,93,96,120],"hypothesise":[8],"times":[9],"at":[10],"which":[11,38,114,133],"any":[12],"of":[13,16,25,37,59,73,101],"a":[14,40,52,57,71,81,124],"set":[15,72],"key":[17,65,105],"terms":[18,106],"occurs":[19],"audio.":[21],"An":[22,91],"important":[23],"aspect":[24],"such":[26],"systems":[27,122],"are":[28,131],"the":[29,35,99,141],"scores":[30,47],"assigned":[31,62],"these":[33,46],"hypotheses,":[34],"accuracy":[36],"have":[39],"significant":[41],"impact":[42],"on":[43],"performance.":[44],"Estimating":[45],"may":[48],"be":[49],"formulated":[50],"as":[51],"confidence":[53,60,89],"estimation":[54],"problem,":[55],"where":[56],"measure":[58],"each":[64],"term":[66],"hypothesis.":[67],"In":[68],"this":[69,94,118,145],"work,":[70],"discriminative":[74],"features":[75],"defined,":[77],"and":[78],"combined":[79],"using":[80,140],"conditional":[82],"random":[83],"field":[84],"(CRF)":[85],"model":[86,95],"for":[87],"improved":[88],"estimation.":[90],"extension":[92],"directly":[97],"address":[98],"problem":[100],"score":[102,112],"normalisation":[103,113],"across":[104],"also":[108],"introduced.":[109],"implicit":[111],"results":[115],"from":[116],"applying":[117],"approach":[119],"separate":[121],"hybrid":[125],"configuration":[126],"yields":[127],"further":[128],"benefits.":[129],"Results":[130],"presented":[132,143],"show":[134],"notable":[135],"improvements":[136],"KWS":[138],"performance":[139],"techniques":[142],"work.":[146]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
