{"id":"https://openalex.org/W1979904744","doi":"https://doi.org/10.1109/taslp.2014.2347133","title":"Latent Semantic Rational Kernels for Topic Spotting on Conversational Speech","display_name":"Latent Semantic Rational Kernels for Topic Spotting on Conversational Speech","publication_year":2014,"publication_date":"2014-08-13","ids":{"openalex":"https://openalex.org/W1979904744","doi":"https://doi.org/10.1109/taslp.2014.2347133","mag":"1979904744"},"language":"en","primary_location":{"id":"doi:10.1109/taslp.2014.2347133","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taslp.2014.2347133","pdf_url":null,"source":{"id":"https://openalex.org/S4210169297","display_name":"IEEE/ACM Transactions on Audio Speech and Language Processing","issn_l":"2329-9290","issn":["2329-9290","2329-9304"],"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/ACM 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/A5106404246","display_name":"Chao Weng","orcid":null},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chao Weng","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA","Department of Electrical & Computer Engineering, Georgia Institute of Technology, Atlanta, GA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"Department of Electrical & Computer Engineering, Georgia Institute of Technology, Atlanta, GA#TAB#","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081673333","display_name":"David L. Thomson","orcid":null},"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":false,"raw_author_name":"David L. Thomson","raw_affiliation_strings":["AT&T Labs-Research, Florham Park, NJ, USA","AT&T Labs\u2014\u2014Research, Florham Park, NJ#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AT&T Labs-Research, Florham Park, NJ, USA","institution_ids":["https://openalex.org/I1283103587"]},{"raw_affiliation_string":"AT&T Labs\u2014\u2014Research, Florham Park, NJ#TAB#","institution_ids":["https://openalex.org/I1283103587"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026605560","display_name":"Patrick Haffner","orcid":"https://orcid.org/0000-0002-2319-5109"},"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":false,"raw_author_name":"Patrick Haffner","raw_affiliation_strings":["AT&T Labs-Research, Florham Park, NJ, USA","AT&T Labs\u2014\u2014Research, Florham Park, NJ#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AT&T Labs-Research, Florham Park, NJ, USA","institution_ids":["https://openalex.org/I1283103587"]},{"raw_affiliation_string":"AT&T Labs\u2014\u2014Research, Florham Park, NJ#TAB#","institution_ids":["https://openalex.org/I1283103587"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110122094","display_name":"Biing-Hwang Juang","orcid":null},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Biing-Hwang Fred Juang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA","Department of Electrical & Computer Engineering, Georgia Institute of Technology, Atlanta, GA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"Department of Electrical & Computer Engineering, Georgia Institute of Technology, Atlanta, GA#TAB#","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4142,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.73021094,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":"22","issue":"12","first_page":"1738","last_page":"1749"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","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/T10201","display_name":"Speech Recognition and Synthesis","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/T12031","display_name":"Speech and dialogue systems","score":0.9991999864578247,"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/T10403","display_name":"Phonetics and Phonology Research","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/spotting","display_name":"Spotting","score":0.7902626395225525},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7849593162536621},{"id":"https://openalex.org/keywords/probabilistic-latent-semantic-analysis","display_name":"Probabilistic latent semantic analysis","score":0.7235046625137329},{"id":"https://openalex.org/keywords/latent-semantic-analysis","display_name":"Latent semantic analysis","score":0.6626322865486145},{"id":"https://openalex.org/keywords/wordnet","display_name":"WordNet","score":0.6341201066970825},{"id":"https://openalex.org/keywords/keyword-spotting","display_name":"Keyword spotting","score":0.6179788112640381},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6099503040313721},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5772170424461365},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.5404092073440552},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5274456143379211},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.45920330286026},{"id":"https://openalex.org/keywords/n-gram","display_name":"n-gram","score":0.41453543305397034},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.32508689165115356},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.27045726776123047}],"concepts":[{"id":"https://openalex.org/C2779506182","wikidata":"https://www.wikidata.org/wiki/Q7580141","display_name":"Spotting","level":2,"score":0.7902626395225525},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7849593162536621},{"id":"https://openalex.org/C112933361","wikidata":"https://www.wikidata.org/wiki/Q2845258","display_name":"Probabilistic latent semantic analysis","level":2,"score":0.7235046625137329},{"id":"https://openalex.org/C170133592","wikidata":"https://www.wikidata.org/wiki/Q1806883","display_name":"Latent semantic analysis","level":2,"score":0.6626322865486145},{"id":"https://openalex.org/C157659113","wikidata":"https://www.wikidata.org/wiki/Q533822","display_name":"WordNet","level":2,"score":0.6341201066970825},{"id":"https://openalex.org/C2781213101","wikidata":"https://www.wikidata.org/wiki/Q6398558","display_name":"Keyword spotting","level":2,"score":0.6179788112640381},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6099503040313721},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5772170424461365},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.5404092073440552},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5274456143379211},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.45920330286026},{"id":"https://openalex.org/C117884012","wikidata":"https://www.wikidata.org/wiki/Q94489","display_name":"n-gram","level":3,"score":0.41453543305397034},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.32508689165115356},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.27045726776123047},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/taslp.2014.2347133","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taslp.2014.2347133","pdf_url":null,"source":{"id":"https://openalex.org/S4210169297","display_name":"IEEE/ACM Transactions on Audio Speech and Language Processing","issn_l":"2329-9290","issn":["2329-9290","2329-9304"],"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/ACM Transactions on Audio, Speech, and Language Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W1495272761","https://openalex.org/W1496147749","https://openalex.org/W1498731359","https://openalex.org/W1524333225","https://openalex.org/W1561056154","https://openalex.org/W1612003148","https://openalex.org/W1647729745","https://openalex.org/W1880262756","https://openalex.org/W1978394996","https://openalex.org/W1980317488","https://openalex.org/W1981276685","https://openalex.org/W2028080169","https://openalex.org/W2038721957","https://openalex.org/W2042980227","https://openalex.org/W2046134527","https://openalex.org/W2046932483","https://openalex.org/W2100935296","https://openalex.org/W2102381086","https://openalex.org/W2107743791","https://openalex.org/W2117805756","https://openalex.org/W2121184547","https://openalex.org/W2130180273","https://openalex.org/W2136480620","https://openalex.org/W2142120379","https://openalex.org/W2146258017","https://openalex.org/W2147152072","https://openalex.org/W2161195767","https://openalex.org/W2165612380","https://openalex.org/W2166023018","https://openalex.org/W2166473218","https://openalex.org/W2171144711","https://openalex.org/W2950225692","https://openalex.org/W2953332543","https://openalex.org/W3007254004","https://openalex.org/W4233135949","https://openalex.org/W4237791300","https://openalex.org/W6631362777","https://openalex.org/W6633640926","https://openalex.org/W6636440780","https://openalex.org/W6636975626","https://openalex.org/W6675339850","https://openalex.org/W6677712588","https://openalex.org/W6683794572","https://openalex.org/W6684245710"],"related_works":["https://openalex.org/W2918559346","https://openalex.org/W2114097550","https://openalex.org/W3119978414","https://openalex.org/W2516975559","https://openalex.org/W2545741539","https://openalex.org/W3206647229","https://openalex.org/W4286904253","https://openalex.org/W1969408022","https://openalex.org/W2000885660","https://openalex.org/W2117995638"],"abstract_inverted_index":{"In":[0],"this":[1],"work,":[2],"we":[3,98,122],"propose":[4],"latent":[5,45,84],"semantic":[6,46,85],"rational":[7,35,135],"kernels":[8],"(LSRK)":[9],"for":[10],"topic":[11,71,90,101,128],"spotting":[12,72,102,129],"on":[13,104],"conversational":[14],"speech.":[15],"Rather":[16],"than":[17],"mapping":[18],"the":[19,37,41,49,70,79,94,100,119,133],"input":[20],"weighted":[21],"finite-state":[22],"transducers":[23],"(WFSTs)":[24],"onto":[25,43],"a":[26,44,63],"high":[27],"dimensional":[28],"n-gram":[29,34,134],"feature":[30],"space":[31],"as":[32],"in":[33],"kernels,":[36],"proposed":[38,50,95,120],"LSRK":[39,80,96,121],"maps":[40],"WFSTs":[42],"space.":[47],"With":[48],"LSRK,":[51],"all":[52],"available":[53],"external":[54],"knowledge":[55],"and":[56,88,108,126],"techniques":[57],"can":[58,123],"be":[59],"flexibly":[60],"integrated":[61],"into":[62],"unified":[64],"WFST":[65],"based":[66],"framework":[67],"to":[68,77],"boost":[69],"performance.":[73],"We":[74],"present":[75],"how":[76],"generalize":[78],"using":[81],"tf-idf":[82],"weighting,":[83],"analysis,":[86],"WordNet":[87],"probabilistic":[89],"models.":[91],"To":[92],"validate":[93],"framework,":[97],"conduct":[99],"experiments":[103],"two":[105],"datasets,":[106],"Switchboard":[107],"AT&T":[109],"HMIHY0300":[110],"initial":[111],"collection.":[112],"The":[113],"experimental":[114],"results":[115],"show":[116],"that":[117],"with":[118],"achieve":[124],"significant":[125],"consistent":[127],"performance":[130],"gains":[131],"over":[132],"kernels.":[136]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}