{"id":"https://openalex.org/W2168363555","doi":"https://doi.org/10.1109/tasl.2011.2139207","title":"MCE Training Techniques for Topic Identification of Spoken Audio Documents","display_name":"MCE Training Techniques for Topic Identification of Spoken Audio Documents","publication_year":2011,"publication_date":"2011-04-08","ids":{"openalex":"https://openalex.org/W2168363555","doi":"https://doi.org/10.1109/tasl.2011.2139207","mag":"2168363555"},"language":"en","primary_location":{"id":"doi:10.1109/tasl.2011.2139207","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tasl.2011.2139207","pdf_url":null,"source":{"id":"https://openalex.org/S199497470","display_name":"IEEE Transactions on Audio Speech and Language Processing","issn_l":"1558-7916","issn":["1558-7916","1558-7924"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Audio, Speech, and Language Processing","raw_type":"journal-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/A5114018312","display_name":"Timothy J. Hazen","orcid":"https://orcid.org/0009-0006-1413-9590"},"institutions":[{"id":"https://openalex.org/I4210122954","display_name":"MIT Lincoln Laboratory","ror":"https://ror.org/022z6jk58","country_code":"US","type":"facility","lineage":["https://openalex.org/I4210122954","https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Timothy J. Hazen","raw_affiliation_strings":["MIT Lincoln Laboratories, Lexington, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MIT Lincoln Laboratories, Lexington, MA, USA","institution_ids":["https://openalex.org/I4210122954"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5114018312"],"corresponding_institution_ids":["https://openalex.org/I4210122954"],"apc_list":null,"apc_paid":null,"fwci":1.2941,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.84993443,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"19","issue":"8","first_page":"2451","last_page":"2460"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9987000226974487,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9987000226974487,"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":0.9976999759674072,"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":0.7898964881896973},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.7054187059402466},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6279770731925964},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6066738963127136},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5281084775924683},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.5171800851821899},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.5065039396286011},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.46619123220443726},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4634658396244049},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.459307998418808},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44877681136131287},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4271976351737976},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4266582131385803},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42120862007141113},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4188443124294281},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07945629954338074}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7898964881896973},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.7054187059402466},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6279770731925964},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6066738963127136},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5281084775924683},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5171800851821899},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.5065039396286011},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.46619123220443726},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4634658396244049},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.459307998418808},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44877681136131287},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4271976351737976},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4266582131385803},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42120862007141113},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4188443124294281},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07945629954338074},{"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/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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tasl.2011.2139207","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tasl.2011.2139207","pdf_url":null,"source":{"id":"https://openalex.org/S199497470","display_name":"IEEE Transactions on Audio Speech and Language Processing","issn_l":"1558-7916","issn":["1558-7916","1558-7924"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Audio, Speech, and Language Processing","raw_type":"journal-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.374.7739","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.374.7739","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.ll.mit.edu/mission/communications/publications/publication-files/full_papers/2011_11_01_HazenT_TASLP_FP.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W20483661","https://openalex.org/W67254146","https://openalex.org/W97072897","https://openalex.org/W202343879","https://openalex.org/W1486089539","https://openalex.org/W1511045614","https://openalex.org/W1549656520","https://openalex.org/W1550863320","https://openalex.org/W1574901103","https://openalex.org/W1618905105","https://openalex.org/W1910663139","https://openalex.org/W1924689489","https://openalex.org/W2038262612","https://openalex.org/W2052706705","https://openalex.org/W2063541597","https://openalex.org/W2105778889","https://openalex.org/W2111732304","https://openalex.org/W2118020653","https://openalex.org/W2120929742","https://openalex.org/W2130180273","https://openalex.org/W2136216715","https://openalex.org/W2136246550","https://openalex.org/W2142749559","https://openalex.org/W2148603752","https://openalex.org/W2149684865","https://openalex.org/W2153635508","https://openalex.org/W2153849757","https://openalex.org/W2157791002","https://openalex.org/W2169985655","https://openalex.org/W2435251607","https://openalex.org/W3004533406","https://openalex.org/W3176583243","https://openalex.org/W4285719527","https://openalex.org/W6640261747","https://openalex.org/W6682304300","https://openalex.org/W6682953061","https://openalex.org/W6717827561"],"related_works":["https://openalex.org/W2090763504","https://openalex.org/W148178222","https://openalex.org/W2394466068","https://openalex.org/W1987683558","https://openalex.org/W2104657898","https://openalex.org/W1948992892","https://openalex.org/W1886884218","https://openalex.org/W2357114597","https://openalex.org/W2115416187","https://openalex.org/W1577730984"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"discuss":[4],"the":[5,70,90],"use":[6],"of":[7,35],"minimum":[8],"classification":[9],"error":[10],"(MCE)":[11],"training":[12,39,50,93],"as":[13,24],"a":[14],"means":[15],"for":[16],"improving":[17],"traditional":[18],"approaches":[19],"to":[20,44,51,58],"topic":[21,86],"identification":[22,87],"such":[23],"naive":[25],"Bayes":[26],"classifiers":[27],"and":[28],"support":[29],"vector":[30,75],"machines.":[31],"A":[32],"key":[33],"element":[34],"our":[36],"new":[37,91],"MCE":[38,92],"techniques":[40,94],"is":[41],"their":[42],"ability":[43],"efficiently":[45],"apply":[46],"jackknifing":[47],"or":[48],"leave-one-out":[49],"yield":[52],"improved":[53],"models":[54],"which":[55],"generalize":[56],"better":[57],"unseen":[59],"data.":[60],"Experiments":[61],"were":[62,95],"conducted":[63],"using":[64,73,89],"recorded":[65],"human-human":[66],"telephone":[67],"conversations":[68],"from":[69,77],"Fisher":[71],"Corpus":[72],"feature":[74],"representations":[76],"word-based":[78],"automatic":[79],"speech":[80],"recognition":[81],"lattices.":[82],"Sizeable":[83],"improvements":[84],"in":[85],"accuracy":[88],"observed.":[96]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}