{"id":"https://openalex.org/W2532440341","doi":"https://doi.org/10.1109/iscslp.2016.7918437","title":"Prosodic annotation enriched statistical machine translation","display_name":"Prosodic annotation enriched statistical machine translation","publication_year":2016,"publication_date":"2016-10-01","ids":{"openalex":"https://openalex.org/W2532440341","doi":"https://doi.org/10.1109/iscslp.2016.7918437","mag":"2532440341"},"language":"en","primary_location":{"id":"doi:10.1109/iscslp.2016.7918437","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscslp.2016.7918437","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 10th International Symposium on Chinese Spoken Language Processing (ISCSLP)","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/A5029129957","display_name":"Peidong Guo","orcid":"https://orcid.org/0009-0004-2635-0065"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peidong Guo","raw_affiliation_strings":["Department of Computer Science and Technology, Beijing Institute of technology, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Beijing Institute of technology, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087631670","display_name":"Heyan Huang","orcid":"https://orcid.org/0000-0002-0320-7520"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Heyan Huang","raw_affiliation_strings":["Department of Computer Science and Technology, Beijing Institute of technology, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Beijing Institute of technology, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101796595","display_name":"Ping Jian","orcid":"https://orcid.org/0000-0001-7236-2922"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ping Jian","raw_affiliation_strings":["Department of Computer Science and Technology, Beijing Institute of technology, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Beijing Institute of technology, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103148859","display_name":"Yuhang Guo","orcid":"https://orcid.org/0009-0005-6343-285X"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuhang Guo","raw_affiliation_strings":["Department of Computer Science and Technology, Beijing Institute of technology, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Beijing Institute of technology, China","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.09516036,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"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":0.9954000115394592,"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":0.8140993118286133},{"id":"https://openalex.org/keywords/machine-translation","display_name":"Machine translation","score":0.6774483919143677},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6692333221435547},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6407005786895752},{"id":"https://openalex.org/keywords/conditional-random-field","display_name":"Conditional random field","score":0.527889609336853},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.48500582575798035},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.4526916444301605},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.43483835458755493},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.1725914478302002}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8140993118286133},{"id":"https://openalex.org/C203005215","wikidata":"https://www.wikidata.org/wiki/Q79798","display_name":"Machine translation","level":2,"score":0.6774483919143677},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6692333221435547},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6407005786895752},{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.527889609336853},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.48500582575798035},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.4526916444301605},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.43483835458755493},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.1725914478302002},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iscslp.2016.7918437","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscslp.2016.7918437","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 10th International Symposium on Chinese Spoken Language Processing (ISCSLP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.8299999833106995,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W162654330","https://openalex.org/W175234851","https://openalex.org/W177677066","https://openalex.org/W222053410","https://openalex.org/W1597460464","https://openalex.org/W2109896588","https://openalex.org/W2113788796","https://openalex.org/W2130416582","https://openalex.org/W2134815611","https://openalex.org/W2143827132","https://openalex.org/W2146574666","https://openalex.org/W2146813944","https://openalex.org/W2153653739","https://openalex.org/W2157435188","https://openalex.org/W2250467593","https://openalex.org/W2348137974","https://openalex.org/W2595715041"],"related_works":["https://openalex.org/W2356597680","https://openalex.org/W2093471820","https://openalex.org/W50079190","https://openalex.org/W2114846443","https://openalex.org/W3102147106","https://openalex.org/W2111726165","https://openalex.org/W2347460059","https://openalex.org/W1984858032","https://openalex.org/W2616891703","https://openalex.org/W2055466819"],"abstract_inverted_index":{"More":[0],"and":[1,24,46,54,58,82,157,179],"more":[2],"linguistic":[3],"information":[4,34],"has":[5],"been":[6],"employed":[7],"to":[8,74,87,115,119,136],"improve":[9,185],"the":[10,32,36,62,76,96,110,120,127,133,138,144,168,175,180,186],"performance":[11],"of":[12,18],"machine":[13],"translation,":[14],"such":[15,38],"as":[16,39,101],"part":[17],"speech,":[19],"syntactic":[20],"structures,":[21],"discourse":[22],"contexts,":[23],"so":[25],"on.":[26],"However,":[27],"conventional":[28],"approaches":[29],"typically":[30],"ignore":[31],"key":[33],"beyond":[35],"text":[37],"prosody.":[40],"In":[41],"this":[42],"paper,":[43],"we":[44],"exploit":[45],"employ":[47],"three":[48,83],"prosodic":[49,56,77,97,111,128,166],"features:":[50,90],"pronunciation":[51],"(phonetic":[52],"alphabet":[53],"tone),":[55],"boundaries":[57,112],"emphasis.":[59],"Based":[60],"on":[61],"annotated":[63],"data,":[64],"a":[65,104],"conditional":[66],"random":[67],"fields":[68],"(CRF)":[69],"sequential":[70],"tagger":[71],"is":[72],"used":[73],"label":[75],"tags":[78],"for":[79],"Chinese":[80],"sentences,":[81],"methods":[84,146],"are":[85,99,113,130],"presented":[86],"integrate":[88],"these":[89],"(1)":[91],"factored":[92,181],"translation":[93,140,160,182],"models":[94,125,183],"where":[95,109,126],"features":[98,129],"incorporated":[100],"factors;":[102],"(2)":[103],"word":[105,176],"lattice":[106,177],"decoding":[107,178],"model":[108,135,170],"considered":[114],"be":[116],"an":[117],"alternative":[118],"tokenization":[121],"boundaries;":[122],"(3)":[123],"re-ranking":[124,169],"integrated":[131],"in":[132,154],"language":[134],"re-score":[137],"n-best":[139],"candidates.":[141],"We":[142],"evaluate":[143],"proposed":[145],"with":[147,165],"bilingual":[148],"evaluation":[149],"understudy":[150],"(BLEU)":[151],"score":[152],"both":[153],"English-to-Chinese":[155],"(E2C)":[156],"Chinese-to-English":[158],"(C2E)":[159],"directions.":[161],"Experiments":[162],"show":[163],"that":[164],"features,":[167],"achieves":[171],"significant":[172],"improvement,":[173],"while":[174],"also":[184],"performance.":[187]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}