{"id":"https://openalex.org/W2140281218","doi":"https://doi.org/10.1109/icassp.2009.4960493","title":"A new method for OOV detection using hybrid word/fragment system","display_name":"A new method for OOV detection using hybrid word/fragment system","publication_year":2009,"publication_date":"2009-04-01","ids":{"openalex":"https://openalex.org/W2140281218","doi":"https://doi.org/10.1109/icassp.2009.4960493","mag":"2140281218"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2009.4960493","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2009.4960493","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 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/A5110230355","display_name":"Ariya Rastrow","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":true,"raw_author_name":"Ariya Rastrow","raw_affiliation_strings":["Center of Language and Speech Processing, Johns Hopkins University, Baltimore, MD, USA","[Center for Language and Speech Processing, Johns Hopkins University, Baltimore, MD, USA]"],"affiliations":[{"raw_affiliation_string":"Center of Language and Speech Processing, Johns Hopkins University, Baltimore, MD, USA","institution_ids":["https://openalex.org/I145311948"]},{"raw_affiliation_string":"[Center for Language and Speech Processing, Johns Hopkins University, Baltimore, MD, USA]","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088302697","display_name":"Abhinav Sethy","orcid":null},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]},{"id":"https://openalex.org/I4210114115","display_name":"IBM Research - Thomas J. Watson Research Center","ror":"https://ror.org/0265w5591","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Abhinav Sethy","raw_affiliation_strings":["IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA","IBM T. J. Watson Research Center, Yorktown Heights , NY, USA#TAB#"],"affiliations":[{"raw_affiliation_string":"IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA","institution_ids":["https://openalex.org/I4210114115"]},{"raw_affiliation_string":"IBM T. J. Watson Research Center, Yorktown Heights , NY, USA#TAB#","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071715737","display_name":"Bhuvana Ramabhadran","orcid":null},"institutions":[{"id":"https://openalex.org/I4210114115","display_name":"IBM Research - Thomas J. Watson Research Center","ror":"https://ror.org/0265w5591","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115"]},{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bhuvana Ramabhadran","raw_affiliation_strings":["IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA","IBM T. J. Watson Research Center, Yorktown Heights , NY, USA#TAB#"],"affiliations":[{"raw_affiliation_string":"IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA","institution_ids":["https://openalex.org/I4210114115"]},{"raw_affiliation_string":"IBM T. J. Watson Research Center, Yorktown Heights , NY, USA#TAB#","institution_ids":["https://openalex.org/I1341412227"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5110230355"],"corresponding_institution_ids":["https://openalex.org/I145311948"],"apc_list":null,"apc_paid":null,"fwci":9.4607,"has_fulltext":false,"cited_by_count":57,"citation_normalized_percentile":{"value":0.98042389,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3953","last_page":"3956"},"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":0.9983000159263611,"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":0.998199999332428,"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":0.8889639377593994},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.7101414799690247},{"id":"https://openalex.org/keywords/vocabulary","display_name":"Vocabulary","score":0.6888203620910645},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6114481091499329},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6036742329597473},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5922122597694397},{"id":"https://openalex.org/keywords/fragment","display_name":"Fragment (logic)","score":0.5797930955886841},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5541969537734985},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.5197576880455017},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4561866521835327},{"id":"https://openalex.org/keywords/hybrid-system","display_name":"Hybrid system","score":0.43833082914352417},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.421358585357666},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4126891791820526},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32489335536956787},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1633608043193817},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.11579149961471558}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8889639377593994},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.7101414799690247},{"id":"https://openalex.org/C2777601683","wikidata":"https://www.wikidata.org/wiki/Q6499736","display_name":"Vocabulary","level":2,"score":0.6888203620910645},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6114481091499329},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6036742329597473},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5922122597694397},{"id":"https://openalex.org/C2776235265","wikidata":"https://www.wikidata.org/wiki/Q18392052","display_name":"Fragment (logic)","level":2,"score":0.5797930955886841},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5541969537734985},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.5197576880455017},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4561866521835327},{"id":"https://openalex.org/C50897621","wikidata":"https://www.wikidata.org/wiki/Q2665508","display_name":"Hybrid system","level":2,"score":0.43833082914352417},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.421358585357666},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4126891791820526},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32489335536956787},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1633608043193817},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.11579149961471558},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icassp.2009.4960493","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2009.4960493","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE International Conference on Acoustics, Speech and Signal Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.433.9223","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.433.9223","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/~arastrow/Publications/OOVhybrid_icassp09.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7300000190734863,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W28518826","https://openalex.org/W39510643","https://openalex.org/W58893626","https://openalex.org/W67332896","https://openalex.org/W183136171","https://openalex.org/W1501139663","https://openalex.org/W1571931074","https://openalex.org/W1978394996","https://openalex.org/W2005076803","https://openalex.org/W2031735445","https://openalex.org/W2113540630","https://openalex.org/W2126315862","https://openalex.org/W2134659216","https://openalex.org/W4230318854","https://openalex.org/W4301749008","https://openalex.org/W6601158046"],"related_works":["https://openalex.org/W1973480752","https://openalex.org/W2805502594","https://openalex.org/W3132641048","https://openalex.org/W4253208712","https://openalex.org/W31439402","https://openalex.org/W2217679042","https://openalex.org/W1603677234","https://openalex.org/W2525971763","https://openalex.org/W2984753899","https://openalex.org/W2783178962"],"abstract_inverted_index":{"In":[0],"this":[1,57],"paper,":[2],"we":[3],"propose":[4],"a":[5,19,31,47,69,74],"new":[6],"method":[7,29,58],"for":[8],"detecting":[9],"regions":[10],"with":[11],"out-of-vocabulary":[12],"(OOV)":[13],"words":[14,35],"in":[15,63],"the":[16,44,50,64,87],"output":[17],"of":[18,46,53],"large":[20],"vocabulary":[21],"continuous":[22],"speech":[23],"recognition":[24],"(LVCSR)":[25],"system.":[26],"The":[27],"proposed":[28],"uses":[30],"hybrid":[32,75],"system":[33],"combining":[34],"and":[36],"data-driven":[37],"variable":[38],"length":[39],"sub":[40,54],"word":[41,55],"units.":[42],"With":[43],"use":[45],"single":[48],"feature,":[49],"posterior":[51],"probability":[52],"units,":[56],"outperforms":[59],"existing":[60],"methods":[61],"published":[62],"literature.":[65],"We":[66],"also":[67],"presents":[68],"recipe":[70],"to":[71,78],"discriminatively":[72],"train":[73],"language":[76],"model":[77],"improve":[79],"OOV":[80],"detection":[81],"rate.":[82],"Results":[83],"are":[84],"presented":[85],"on":[86],"RT04":[88],"broadcast":[89],"news":[90],"task.":[91]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":5},{"year":2013,"cited_by_count":6},{"year":2012,"cited_by_count":7}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}