{"id":"https://openalex.org/W2109622018","doi":"https://doi.org/10.1109/icassp.2005.1415175","title":"Joint Discriminative Language Modeling and Utterance Classification","display_name":"Joint Discriminative Language Modeling and Utterance Classification","publication_year":2006,"publication_date":"2006-10-11","ids":{"openalex":"https://openalex.org/W2109622018","doi":"https://doi.org/10.1109/icassp.2005.1415175","mag":"2109622018"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2005.1415175","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2005.1415175","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005.","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/A5055086464","display_name":"Murat Sara\u00e7lar","orcid":"https://orcid.org/0000-0002-7435-8510"},"institutions":[{"id":"https://openalex.org/I1283103587","display_name":"AT&T (United States)","ror":"https://ror.org/02bbd5539","country_code":"US","type":"company","lineage":["https://openalex.org/I1283103587"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"M. Saraclar","raw_affiliation_strings":["AT and T Research Laboratories, Florham Park, NJ, USA","AT&T Lab. Res., USA"],"affiliations":[{"raw_affiliation_string":"AT and T Research Laboratories, Florham Park, NJ, USA","institution_ids":["https://openalex.org/I1283103587"]},{"raw_affiliation_string":"AT&T Lab. Res., USA","institution_ids":["https://openalex.org/I1283103587"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020068498","display_name":"Brian Roark","orcid":null},"institutions":[{"id":"https://openalex.org/I165690674","display_name":"Oregon Health & Science University","ror":"https://ror.org/009avj582","country_code":"US","type":"education","lineage":["https://openalex.org/I165690674"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"B. Roark","raw_affiliation_strings":["Center for Spoken Language Understanding, OGI School of Science & Engineering, Oregon Health and Sciences University, Beaverton, OR, USA","Oregon Health and Science University"],"affiliations":[{"raw_affiliation_string":"Center for Spoken Language Understanding, OGI School of Science & Engineering, Oregon Health and Sciences University, Beaverton, OR, USA","institution_ids":["https://openalex.org/I165690674"]},{"raw_affiliation_string":"Oregon Health and Science University","institution_ids":["https://openalex.org/I165690674"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5055086464"],"corresponding_institution_ids":["https://openalex.org/I1283103587"],"apc_list":null,"apc_paid":null,"fwci":2.326,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.8952458,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"1","issue":null,"first_page":"561","last_page":"564"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9986000061035156,"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":0.9970999956130981,"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/discriminative-model","display_name":"Discriminative model","score":0.8046589493751526},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7404348850250244},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6049656271934509},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.6041322946548462},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.600455641746521},{"id":"https://openalex.org/keywords/utterance","display_name":"Utterance","score":0.5008924007415771},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.49773719906806946},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4957183599472046},{"id":"https://openalex.org/keywords/vocabulary","display_name":"Vocabulary","score":0.49341335892677307},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.4616455137729645},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4370647668838501},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4203816056251526},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15797865390777588}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8046589493751526},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7404348850250244},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6049656271934509},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.6041322946548462},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.600455641746521},{"id":"https://openalex.org/C2775852435","wikidata":"https://www.wikidata.org/wiki/Q258403","display_name":"Utterance","level":2,"score":0.5008924007415771},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.49773719906806946},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4957183599472046},{"id":"https://openalex.org/C2777601683","wikidata":"https://www.wikidata.org/wiki/Q6499736","display_name":"Vocabulary","level":2,"score":0.49341335892677307},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.4616455137729645},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4370647668838501},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4203816056251526},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15797865390777588},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icassp.2005.1415175","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2005.1415175","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005.","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.324.3732","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.324.3732","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://speech.bme.ogi.edu/people/roark/ICASSP05.joint.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7300000190734863}],"awards":[],"funders":[{"id":"https://openalex.org/F4320338335","display_name":"H2020 European Research Council","ror":"https://ror.org/0472cxd90"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1491745322","https://openalex.org/W1550863320","https://openalex.org/W2008652694","https://openalex.org/W2047632477","https://openalex.org/W2053463056","https://openalex.org/W2107753812","https://openalex.org/W2124445791","https://openalex.org/W2128854142","https://openalex.org/W2132714218","https://openalex.org/W2147880316","https://openalex.org/W2158148237","https://openalex.org/W2161017816","https://openalex.org/W2161195767","https://openalex.org/W2170919426","https://openalex.org/W2171144711","https://openalex.org/W3007254004","https://openalex.org/W6676372292","https://openalex.org/W6682082992","https://openalex.org/W6683794572"],"related_works":["https://openalex.org/W2113687551","https://openalex.org/W2112752961","https://openalex.org/W2162582511","https://openalex.org/W1523025284","https://openalex.org/W1566315437","https://openalex.org/W4221142855","https://openalex.org/W2594897229","https://openalex.org/W2151348424","https://openalex.org/W2050138804","https://openalex.org/W767271433"],"abstract_inverted_index":{"This":[0],"paper":[1],"investigates":[2],"discriminative":[3],"language":[4,31],"modeling":[5],"in":[6,16,21,65,84],"a":[7,45,66,71,81],"scenario":[8],"with":[9,119],"two":[10],"kinds":[11],"of":[12,57,90],"observed":[13],"errors:":[14],"errors":[15,20],"ASR":[17],"transcription":[18],"and":[19,32,60,101,112],"utterance":[22],"classification.":[23],"Using":[24],"the":[25,95,117],"perceptron":[26],"algorithm,":[27],"we":[28,52],"train":[29],"joint":[30],"class":[33],"models":[34,105],"either":[35],"independently":[36],"or":[37],"simultaneously,":[38],"under":[39],"various":[40,96],"parameter":[41,91],"update":[42,92],"conditions.":[43],"On":[44],"large":[46],"vocabulary":[47],"customer":[48],"service":[49],"call-classification":[50],"application,":[51],"show":[53],"that":[54],"simultaneous":[55],"optimization":[56],"class,":[58],"n-gram,":[59],"class/n-gram":[61],"feature":[62,97],"weights":[63],"results":[64],"significant":[67],"WER":[68],"reduction":[69],"over":[70],"model":[72,118],"using":[73],"just":[74],"n-gram":[75],"features,":[76],"while":[77],"additionally":[78],"significantly":[79],"outperforming":[80],"deployed":[82],"baseline":[83],"classification":[85],"error":[86],"rate.":[87],"A":[88],"range":[89],"approaches":[93],"for":[94],"sets":[98],"are":[99,106,113],"presented":[100],"evaluated.":[102],"The":[103],"resulting":[104],"encoded":[107],"as":[108],"weighted":[109],"finite-state":[110],"automata,":[111],"used":[114],"by":[115],"intersecting":[116],"word":[120],"lattices.":[121]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
