{"id":"https://openalex.org/W2021087960","doi":"https://doi.org/10.1109/asru.2011.6163955","title":"Bootstrapping a spoken language identification system using unsupervised integrated sensing and processing decision trees","display_name":"Bootstrapping a spoken language identification system using unsupervised integrated sensing and processing decision trees","publication_year":2011,"publication_date":"2011-12-01","ids":{"openalex":"https://openalex.org/W2021087960","doi":"https://doi.org/10.1109/asru.2011.6163955","mag":"2021087960"},"language":"en","primary_location":{"id":"doi:10.1109/asru.2011.6163955","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asru.2011.6163955","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE Workshop on Automatic Speech Recognition & Understanding","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/A5074948475","display_name":"Shuai Huang","orcid":"https://orcid.org/0000-0003-3054-5629"},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Shuai Huang","raw_affiliation_strings":["Center for Language and Speech Processing, Johns Hopkins University, USA"],"affiliations":[{"raw_affiliation_string":"Center for Language and Speech Processing, Johns Hopkins University, USA","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054865609","display_name":"Damianos Karakos","orcid":null},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Damianos Karakos","raw_affiliation_strings":["Johns Hopkins University, Baltimore, MD, US","Center for Language and Speech Processing, Johns Hopkins University, USA"],"affiliations":[{"raw_affiliation_string":"Johns Hopkins University, Baltimore, MD, US","institution_ids":["https://openalex.org/I145311948"]},{"raw_affiliation_string":"Center for Language and Speech Processing, Johns Hopkins University, USA","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035622491","display_name":"Glen Coppersmith","orcid":"https://orcid.org/0000-0002-3494-7388"},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Glen A. Coppersmith","raw_affiliation_strings":["Johns Hopkins University, Baltimore, MD, US","Center for Language and Speech Processing, Johns Hopkins University, USA"],"affiliations":[{"raw_affiliation_string":"Johns Hopkins University, Baltimore, MD, US","institution_ids":["https://openalex.org/I145311948"]},{"raw_affiliation_string":"Center for Language and Speech Processing, Johns Hopkins University, USA","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016543371","display_name":"Kenneth Church","orcid":"https://orcid.org/0000-0001-8378-6069"},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kenneth W. Church","raw_affiliation_strings":["Johns Hopkins University, Baltimore, MD, US","Center for Language and Speech Processing, Johns Hopkins University, USA"],"affiliations":[{"raw_affiliation_string":"Johns Hopkins University, Baltimore, MD, US","institution_ids":["https://openalex.org/I145311948"]},{"raw_affiliation_string":"Center for Language and Speech Processing, Johns Hopkins University, USA","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079659476","display_name":"Sabato Marco Siniscalchi","orcid":"https://orcid.org/0000-0002-0770-0507"},"institutions":[{"id":"https://openalex.org/I246010334","display_name":"Universit\u00e0 degli Studi di Enna Kore","ror":"https://ror.org/04vd28p53","country_code":"IT","type":"education","lineage":["https://openalex.org/I246010334"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Sabato Marco Siniscalchi","raw_affiliation_strings":["Kore University of Enna, Enna, Italy","\u201dKore\u201d University of  ENNA, Italy"],"affiliations":[{"raw_affiliation_string":"Kore University of Enna, Enna, Italy","institution_ids":["https://openalex.org/I246010334"]},{"raw_affiliation_string":"\u201dKore\u201d University of  ENNA, Italy","institution_ids":["https://openalex.org/I246010334"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5074948475"],"corresponding_institution_ids":["https://openalex.org/I145311948"],"apc_list":null,"apc_paid":null,"fwci":0.4402,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.72469153,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"39","issue":null,"first_page":"342","last_page":"347"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"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"}},"topics":[{"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9965000152587891,"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":0.8068858981132507},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7038511037826538},{"id":"https://openalex.org/keywords/bootstrapping","display_name":"Bootstrapping (finance)","score":0.6973219513893127},{"id":"https://openalex.org/keywords/nist","display_name":"NIST","score":0.6758596301078796},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6263866424560547},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6070361137390137},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.5395532846450806},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5343830585479736},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5276148319244385},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.5244137048721313},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4916232228279114},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.47297942638397217},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.4707805812358856},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.46233245730400085},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.44883155822753906},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.35562190413475037}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8068858981132507},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7038511037826538},{"id":"https://openalex.org/C207609745","wikidata":"https://www.wikidata.org/wiki/Q4944086","display_name":"Bootstrapping (finance)","level":2,"score":0.6973219513893127},{"id":"https://openalex.org/C111219384","wikidata":"https://www.wikidata.org/wiki/Q6954384","display_name":"NIST","level":2,"score":0.6758596301078796},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6263866424560547},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6070361137390137},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.5395532846450806},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5343830585479736},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5276148319244385},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.5244137048721313},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4916232228279114},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.47297942638397217},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.4707805812358856},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.46233245730400085},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.44883155822753906},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.35562190413475037},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","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},{"id":"https://openalex.org/C106159729","wikidata":"https://www.wikidata.org/wiki/Q2294553","display_name":"Financial economics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/asru.2011.6163955","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asru.2011.6163955","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE Workshop on Automatic Speech Recognition & Understanding","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.220.8028","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.220.8028","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/%7Edamianos/asru11_lid.pdf","raw_type":"text"},{"id":"pmh:oai:iris.unipa.it:10447/664126","is_oa":false,"landing_page_url":"https://hdl.handle.net/10447/664126","pdf_url":null,"source":{"id":"https://openalex.org/S4306401065","display_name":"Nova Science Publishers (Nova Science Publishers, Inc.)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/bookPart"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4300000071525574,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W151003953","https://openalex.org/W173660884","https://openalex.org/W260531045","https://openalex.org/W1479807131","https://openalex.org/W1495019370","https://openalex.org/W1686946872","https://openalex.org/W1971273973","https://openalex.org/W1991068165","https://openalex.org/W2080209778","https://openalex.org/W2125038697","https://openalex.org/W2154339456","https://openalex.org/W2163352728","https://openalex.org/W2163817918","https://openalex.org/W2172000360","https://openalex.org/W2398046886","https://openalex.org/W6637108112","https://openalex.org/W6683680113"],"related_works":["https://openalex.org/W2106922437","https://openalex.org/W2807901368","https://openalex.org/W2158491338","https://openalex.org/W2133733652","https://openalex.org/W2072658171","https://openalex.org/W165115930","https://openalex.org/W2096363773","https://openalex.org/W2794908468","https://openalex.org/W4299840061","https://openalex.org/W2531570999"],"abstract_inverted_index":{"In":[0,47,150],"many":[1],"inference":[2],"and":[3,16,18,128,142,158],"learning":[4,41,74],"tasks,":[5],"collecting":[6],"large":[7],"amounts":[8,28,59,137],"of":[9,29,35,39,55,60,138,180],"labeled":[10,30,61,111],"training":[11,183],"data":[12,31,86,112,139],"is":[13,80],"time":[14],"consuming":[15],"expensive,":[17],"oftentimes":[19],"impractical.":[20],"Thus,":[21],"being":[22],"able":[23],"to":[24,71,82,98,113,134,140],"efficiently":[25],"use":[26,144],"small":[27,58,136],"with":[32],"an":[33,76,102,115],"abundance":[34],"unlabeled":[36,85],"data-the":[37],"topic":[38],"semi-supervised":[40],"(SSL)":[42],"[1]-has":[43],"garnered":[44],"much":[45],"attention.":[46],"this":[48],"paper,":[49],"we":[50,106,166],"look":[51],"at":[52],"the":[53,63,84,156,169],"problem":[54],"choosing":[56],"these":[57],"data,":[62],"first":[64],"step":[65],"in":[66,101,124,145,173],"a":[67,151],"bootstrapping":[68],"paradigm.":[69],"Contrary":[70],"traditional":[72],"active":[73],"where":[75],"initial":[77,116],"trained":[78],"model":[79],"employed":[81],"select":[83,135],"points":[87],"which":[88],"would":[89],"be":[90,99],"most":[91],"informative":[92],"if":[93],"labeled,":[94],"our":[95],"selection":[96,179],"has":[97],"done":[100],"unsupervised":[103,121],"way,":[104],"as":[105],"do":[107],"not":[108],"even":[109],"have":[110],"train":[114],"model.":[117],"We":[118],"propose":[119],"using":[120],"clustering":[122],"algorithms,":[123],"particular":[125],"integrated":[126],"sensing":[127],"processing":[129],"decision":[130],"trees":[131],"(ISPDTs)":[132],"[2],":[133],"label":[141],"subsequently":[143],"SSL":[146],"(e.g.":[147],"transductive":[148],"SVMs).":[149],"language":[152],"identification":[153],"task":[154],"on":[155],"CallFriend1":[157],"2003":[159],"NIST":[160],"Language":[161],"Recognition":[162],"Evaluation":[163],"corpora":[164],"[3],":[165],"demonstrate":[167],"that":[168],"proposed":[170],"method":[171],"results":[172],"significantly":[174],"improved":[175],"performance":[176],"over":[177],"random":[178],"equivalently":[181],"sized":[182],"data.":[184]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}