{"id":"https://openalex.org/W2398171323","doi":"https://doi.org/10.21437/interspeech.2013-611","title":"Corpus analysis of simultaneous interpretation data for improving real time speech translation","display_name":"Corpus analysis of simultaneous interpretation data for improving real time speech translation","publication_year":2013,"publication_date":"2013-08-25","ids":{"openalex":"https://openalex.org/W2398171323","doi":"https://doi.org/10.21437/interspeech.2013-611","mag":"2398171323"},"language":"en","primary_location":{"id":"doi:10.21437/interspeech.2013-611","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2013-611","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2013","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/A5112911746","display_name":"Vivek Kumar Rangarajan Sridhar","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":true,"raw_author_name":"Vivek Kumar Rangarajan Sridhar","raw_affiliation_strings":["AT&T\u2021"],"affiliations":[{"raw_affiliation_string":"AT&T\u2021","institution_ids":["https://openalex.org/I1283103587"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101650717","display_name":"John Chen","orcid":"https://orcid.org/0000-0002-9443-4795"},"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":"John Chen","raw_affiliation_strings":["AT&T\u2021"],"affiliations":[{"raw_affiliation_string":"AT&T\u2021","institution_ids":["https://openalex.org/I1283103587"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111475783","display_name":"Srinivas Bangalore","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":"Srinivas Bangalore","raw_affiliation_strings":["AT&T\u2021"],"affiliations":[{"raw_affiliation_string":"AT&T\u2021","institution_ids":["https://openalex.org/I1283103587"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5112911746"],"corresponding_institution_ids":["https://openalex.org/I1283103587"],"apc_list":null,"apc_paid":null,"fwci":1.9926,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.8955139,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"3468","last_page":"3472"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":1.0,"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":1.0,"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":0.9995999932289124,"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/computer-science","display_name":"Computer science","score":0.8411804437637329},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6117562055587769},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.555946409702301},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5358840823173523},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5332871079444885},{"id":"https://openalex.org/keywords/interpretation","display_name":"Interpretation (philosophy)","score":0.5250696539878845},{"id":"https://openalex.org/keywords/speech-translation","display_name":"Speech translation","score":0.5197876691818237},{"id":"https://openalex.org/keywords/interpreter","display_name":"Interpreter","score":0.4721251428127289},{"id":"https://openalex.org/keywords/dynamic-and-formal-equivalence","display_name":"Dynamic and formal equivalence","score":0.43128734827041626},{"id":"https://openalex.org/keywords/speech-processing","display_name":"Speech processing","score":0.4159356951713562},{"id":"https://openalex.org/keywords/machine-translation","display_name":"Machine translation","score":0.3387010097503662}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8411804437637329},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6117562055587769},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.555946409702301},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5358840823173523},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5332871079444885},{"id":"https://openalex.org/C527412718","wikidata":"https://www.wikidata.org/wiki/Q855395","display_name":"Interpretation (philosophy)","level":2,"score":0.5250696539878845},{"id":"https://openalex.org/C2780366754","wikidata":"https://www.wikidata.org/wiki/Q7494857","display_name":"Speech translation","level":3,"score":0.5197876691818237},{"id":"https://openalex.org/C122783720","wikidata":"https://www.wikidata.org/wiki/Q183065","display_name":"Interpreter","level":2,"score":0.4721251428127289},{"id":"https://openalex.org/C98199350","wikidata":"https://www.wikidata.org/wiki/Q978442","display_name":"Dynamic and formal equivalence","level":3,"score":0.43128734827041626},{"id":"https://openalex.org/C61328038","wikidata":"https://www.wikidata.org/wiki/Q3358061","display_name":"Speech processing","level":2,"score":0.4159356951713562},{"id":"https://openalex.org/C203005215","wikidata":"https://www.wikidata.org/wiki/Q79798","display_name":"Machine translation","level":2,"score":0.3387010097503662},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.21437/interspeech.2013-611","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2013-611","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2013","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4099999964237213,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W66137051","https://openalex.org/W174848427","https://openalex.org/W1169983757","https://openalex.org/W1984314602","https://openalex.org/W2089629691","https://openalex.org/W2156985047","https://openalex.org/W2161374612","https://openalex.org/W2165861304","https://openalex.org/W2167435923","https://openalex.org/W2168374548","https://openalex.org/W2251645580","https://openalex.org/W2278668382","https://openalex.org/W2394530649","https://openalex.org/W2916456038","https://openalex.org/W3196619058"],"related_works":["https://openalex.org/W1721418433","https://openalex.org/W2463512549","https://openalex.org/W4386954442","https://openalex.org/W2251328660","https://openalex.org/W4237743574","https://openalex.org/W307032977","https://openalex.org/W4239803647","https://openalex.org/W1516264999","https://openalex.org/W2081440241","https://openalex.org/W4246251581"],"abstract_inverted_index":{"Real-time":[0],"speech-to-speech":[1,21],"(S2S)":[2],"translation":[3,10,22,28,36,48,52,107,145],"of":[4,47,79,94,108,124,154,157,170],"lectures":[5],"and":[6,87,92,98,119,134,162,177],"speeches":[7,159],"require":[8],"simultaneous":[9,20,63,132,144,155,183],"with":[11,70],"low":[12,72],"latency":[13],"to":[14,41,51,61,130],"continually":[15],"engage":[16],"the":[17,45,182],"listeners.":[18],"However,":[19],"systems":[23],"have":[24],"been":[25],"predominantly":[26],"repurposing":[27],"models":[29],"that":[30],"are":[31,59],"typically":[32],"trained":[33],"for":[34],"consecutive":[35],"without":[37],"a":[38,77,111,121,142,152],"motivated":[39],"attempt":[40],"model":[42],"incrementality.":[43],"Furthermore,":[44],"notion":[46],"is":[49],"simplified":[50],"plus":[53],"simultaneity.":[54],"In":[55],"contrast,":[56],"human":[57,128],"interpreters":[58,129],"able":[60],"perform":[62,131,148],"interpretation":[64,133,156,184],"by":[65,75,127],"generating":[66],"target":[67],"speech":[68],"incrementally":[69],"very":[71],"ear-voice":[73],"span":[74],"using":[76],"variety":[78],"strategies":[80],"such":[81,100,172],"as":[82,173,179],"compression":[83],"(paraphrasing),":[84],"incremental":[85],"comprehension,":[86],"anticipation":[88],"through":[89],"discourse":[90,95],"inference":[91,178],"expectation":[93],"redundancies.":[96],"Exploiting":[97],"modeling":[99],"phenomena":[101,125],"can":[102,138],"potentially":[103],"improve":[104],"automatic":[105],"real-time":[106],"speech.":[109],"As":[110],"first":[112],"step,":[113],"in":[114,141,160,181],"this":[115],"work":[116],"we":[117,165],"identify":[118],"present":[120,166],"systematic":[122],"analysis":[123,169],"used":[126],"elucidate":[135],"how":[136],"it":[137],"be":[139],"exploited":[140],"conventional":[143],"framework.":[146],"We":[147],"our":[149],"study":[150],"on":[151],"corpus":[153],"Parliamentary":[158],"English":[161],"Spanish.":[163],"Specifically,":[164],"an":[167],"empirical":[168],"factors":[171],"time":[174],"constraint,":[175],"redundancy":[176],"evidenced":[180],"corpus.":[185]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":1}],"updated_date":"2026-03-31T07:56:22.981413","created_date":"2025-10-10T00:00:00"}