{"id":"https://openalex.org/W110795767","doi":"https://doi.org/10.21437/eurospeech.1999-17","title":"Use of recursive mumble models for confidence measuring","display_name":"Use of recursive mumble models for confidence measuring","publication_year":1999,"publication_date":"1999-09-05","ids":{"openalex":"https://openalex.org/W110795767","doi":"https://doi.org/10.21437/eurospeech.1999-17","mag":"110795767"},"language":"en","primary_location":{"id":"doi:10.21437/eurospeech.1999-17","is_oa":false,"landing_page_url":"https://doi.org/10.21437/eurospeech.1999-17","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"6th European Conference on Speech Communication and Technology","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/A5103431069","display_name":"Qiguang Lin","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"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qiguang Lin","raw_affiliation_strings":["IBM, ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM, ,","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110878210","display_name":"David Lubensky","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"David Lubensky","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5043396055","display_name":"Salim Roukos","orcid":"https://orcid.org/0000-0003-2140-4349"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Salim Roukos","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2785,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.45427241,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"53","last_page":"56"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9962999820709229,"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":0.9962999820709229,"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/T10028","display_name":"Topic Modeling","score":0.9926000237464905,"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":0.9732000231742859,"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/word","display_name":"Word (group theory)","score":0.771930456161499},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7650128602981567},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.7551599740982056},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.7485946416854858},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.7295684814453125},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.483024924993515},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.47781088948249817},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4661848247051239},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.42347198724746704},{"id":"https://openalex.org/keywords/error-detection-and-correction","display_name":"Error detection and correction","score":0.41279250383377075},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36688411235809326},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3500973582267761},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3298637866973877},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.23117002844810486},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17821428179740906}],"concepts":[{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.771930456161499},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7650128602981567},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.7551599740982056},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.7485946416854858},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.7295684814453125},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.483024924993515},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.47781088948249817},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4661848247051239},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.42347198724746704},{"id":"https://openalex.org/C103088060","wikidata":"https://www.wikidata.org/wiki/Q1062839","display_name":"Error detection and correction","level":2,"score":0.41279250383377075},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36688411235809326},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3500973582267761},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3298637866973877},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.23117002844810486},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17821428179740906},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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":1,"locations":[{"id":"doi:10.21437/eurospeech.1999-17","is_oa":false,"landing_page_url":"https://doi.org/10.21437/eurospeech.1999-17","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"6th European Conference on Speech Communication and Technology","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.7200000286102295,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":2,"referenced_works":["https://openalex.org/W2086267546","https://openalex.org/W2135936685"],"related_works":["https://openalex.org/W2980068837","https://openalex.org/W2098872742","https://openalex.org/W2594897229","https://openalex.org/W2151348424","https://openalex.org/W4221142855","https://openalex.org/W2050138804","https://openalex.org/W2129812225","https://openalex.org/W2944691285","https://openalex.org/W4290708361","https://openalex.org/W26527944"],"abstract_inverted_index":{"In":[0,45,156],"many":[1],"speech":[2],"recognition":[3,20],"applications":[4],"such":[5],"as":[6,102],"name":[7],"dialing,":[8],"it":[9,179],"is":[10,37,54,58,84,100,108,122,165],"necessary":[11],"to":[12,16,111,116,167,175],"have":[13],"the":[14,79,92,97,103,119,142,152,158,162,169,189],"ability":[15],"know":[17],"when":[18],"a":[19,48,67,112],"error":[21,171],"has":[22,130],"occurred":[23],"so":[24],"that":[25,141,161,178],"undesired":[26],"or":[27,126],"unpredicted":[28],"system":[29],"behavior":[30],"can":[31],"be":[32],"minimized.":[33],"Con":[34],"dence":[35,105],"measure":[36],"usually":[38],"used":[39,101],"for":[40,51],"detection":[41],"of":[42,62,81],"probable":[43],"errors.":[44],"this":[46],"paper,":[47],"new":[49,143,163],"method":[50,57,129,144,148,164],"measuring":[52],"condence":[53],"presented.":[55],"The":[56,87,128,138],"based":[59,150],"on":[60,151],"use":[61],"recursive":[63,82],"mumble":[64,98],"models.":[65],"During":[66],"regular":[68],"decoding":[69],"from":[70,173],"which":[71],"word":[72,75,93,153],"hypotheses":[73],"and":[74,96,177],"boundaries":[76],"are":[77],"known,":[78],"score":[80,95,99],"mumblemodels":[83],"then":[85],"determined.":[86],"(weighted)":[88],"di":[89,135],"erence":[90],"between":[91],"detail-match":[94,154],"con":[104,123],"measure.":[106],"It":[107],"next":[109],"compared":[110],"prede":[113],"ned":[114],"threshold":[115],"decide":[117],"whether":[118],"decoded":[120],"result":[121],"dently":[124],"correct":[125],"not.":[127],"been":[131],"evaluated":[132],"with":[133],"two":[134],"erent":[136],"databases.":[137],"results":[139,159],"show":[140,160],"outperforms":[145],"our":[146],"previous":[147],"solely":[149],"scores.":[155],"particular,":[157],"able":[166],"reduce":[168],"equal":[170],"rate":[172],"32%":[174],"23%":[176],"rejects":[180],"far":[181],"more":[182],"(78%":[183],"versus":[184],"35%)":[185],"out-of-domain":[186],"sentences":[187],"at":[188],"xed":[190],"5%":[191],"false":[192],"rejection":[193],"rate.":[194]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}