{"id":"https://openalex.org/W2401725913","doi":"https://doi.org/10.21437/interspeech.2012-639","title":"Exploiting discriminative point process models for spoken term detection","display_name":"Exploiting discriminative point process models for spoken term detection","publication_year":2012,"publication_date":"2012-09-09","ids":{"openalex":"https://openalex.org/W2401725913","doi":"https://doi.org/10.21437/interspeech.2012-639","mag":"2401725913"},"language":"en","primary_location":{"id":"doi:10.21437/interspeech.2012-639","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2012-639","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2012","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/A5030074803","display_name":"Atta Norouzian","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Atta Norouzian","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103622427","display_name":"Aren Jansen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Aren Jansen","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077077136","display_name":"Richard C. Rose","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Richard C. Rose","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5101787514","display_name":"Samuel Thomas","orcid":"https://orcid.org/0000-0001-7573-0620"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Samuel Thomas","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5030074803"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.6528,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.91142269,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"2442","last_page":"2445"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9991999864578247,"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":0.9991999864578247,"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":0.9972000122070312,"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/T10860","display_name":"Speech and Audio Processing","score":0.9968000054359436,"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":0.8248820304870605},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7485666871070862},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.7395398020744324},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.587881863117218},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5062450766563416},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.47275835275650024},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.47222307324409485},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.4701929986476898},{"id":"https://openalex.org/keywords/vocabulary","display_name":"Vocabulary","score":0.4629761576652527},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.4502866864204407},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.4500581920146942},{"id":"https://openalex.org/keywords/point-process","display_name":"Point process","score":0.44045209884643555},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.4310167133808136},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42256981134414673},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.41369596123695374},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4101774990558624},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.297296404838562},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.1692872941493988},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11007490754127502},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08054372668266296}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8248820304870605},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7485666871070862},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.7395398020744324},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.587881863117218},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5062450766563416},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.47275835275650024},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.47222307324409485},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.4701929986476898},{"id":"https://openalex.org/C2777601683","wikidata":"https://www.wikidata.org/wiki/Q6499736","display_name":"Vocabulary","level":2,"score":0.4629761576652527},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.4502866864204407},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.4500581920146942},{"id":"https://openalex.org/C88871306","wikidata":"https://www.wikidata.org/wiki/Q7208287","display_name":"Point process","level":2,"score":0.44045209884643555},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.4310167133808136},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42256981134414673},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.41369596123695374},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4101774990558624},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.297296404838562},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1692872941493988},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11007490754127502},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08054372668266296},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"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/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/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.21437/interspeech.2012-639","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2012-639","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2012","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.261.2754","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.261.2754","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.clsp.jhu.edu/%7Esamuel/pdfs/ppm_std.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7400000095367432,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W23025778","https://openalex.org/W114193738","https://openalex.org/W1569447338","https://openalex.org/W2089136440","https://openalex.org/W2100200254","https://openalex.org/W2111928519","https://openalex.org/W2119689163","https://openalex.org/W2147467930","https://openalex.org/W2158948112","https://openalex.org/W2169526216","https://openalex.org/W2170580867","https://openalex.org/W2401207139"],"related_works":["https://openalex.org/W2053269318","https://openalex.org/W2364370872","https://openalex.org/W2025614924","https://openalex.org/W4324119469","https://openalex.org/W2164868312","https://openalex.org/W2160650576","https://openalex.org/W161037869","https://openalex.org/W2170952786","https://openalex.org/W1992295166","https://openalex.org/W2143508933"],"abstract_inverted_index":{"State-of-the-art":[0],"spoken":[1,145],"term":[2,36,146],"detection":[3],"(STD)":[4],"systems":[5],"are":[6,130],"built":[7],"on":[8],"top":[9],"of":[10,23,34],"large":[11],"vocabulary":[12],"speech":[13,140],"recognition":[14,141],"engines,":[15],"which":[16],"generate":[17,82],"lattices":[18,28],"that":[19,121],"encode":[20],"candidate":[21],"occurrences":[22],"each":[24],"invocabulary":[25],"query.":[26],"These":[27],"specifiy":[29],"start":[30],"and":[31,74,107,129],"stop":[32],"times":[33],"hypothesized":[35],"occurrences,":[37],"providing":[38],"a":[39,59,93,138],"clear":[40],"opportunity":[41],"to":[42,44,47,64,81,92,132],"return":[43],"the":[45,65,76],"acoustics":[46],"incorporate":[48],"novel":[49,60],"confidence":[50,84],"measures":[51],"for":[52,104],"verification.":[53],"In":[54,86],"this":[55],"paper,":[56],"we":[57,89],"introduce":[58,90],"exemplar":[61],"distance":[62],"metric":[63],"recently":[66],"proposed":[67],"discriminative":[68,151],"point":[69,116,148],"process":[70,117,149],"modeling":[71,97],"(DPPM)":[72],"framework":[73],"use":[75],"resulting":[77],"whole":[78,122,153],"word":[79,123,154],"models":[80,102,112],"STD":[83,91],"scores.":[85],"doing":[87],"so,":[88],"completely":[94],"distinct":[95],"acoustic":[96],"pipeline,":[98],"trading":[99],"Gaussian":[100],"mixture":[101],"(GMM)":[103],"multi-layer":[105],"perceptrons":[106],"replacing":[108],"dictionary-derived":[109],"hidden":[110],"Markov":[111],"(HMM)":[113],"with":[114],"exemplar-based":[115],"models.":[118],"We":[119],"find":[120],"DPPM":[124],"scores":[125,135],"both":[126],"perform":[127],"comparably":[128],"complementary":[131],"lattice":[133],"posterior":[134],"produced":[136],"by":[137],"state-of-the-art":[139],"engine.":[142],"Index":[143],"Terms:":[144],"detection,":[147],"model,":[150],"training,":[152],"model":[155]},"counts_by_year":[{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":5},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":4}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
