{"id":"https://openalex.org/W2130385155","doi":"https://doi.org/10.21437/interspeech.2006-594","title":"Incorporating second-order information into two-step major phrase break prediction for Korean","display_name":"Incorporating second-order information into two-step major phrase break prediction for Korean","publication_year":2006,"publication_date":"2006-09-17","ids":{"openalex":"https://openalex.org/W2130385155","doi":"https://doi.org/10.21437/interspeech.2006-594","mag":"2130385155"},"language":"en","primary_location":{"id":"doi:10.21437/interspeech.2006-594","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2006-594","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2006","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/A5100656391","display_name":"Seungwon Kim","orcid":"https://orcid.org/0000-0003-4221-3058"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Seungwon Kim","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058978491","display_name":"Jinsik Lee","orcid":"https://orcid.org/0000-0002-1040-0513"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jinsik Lee","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110803611","display_name":"Byeongchang Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Byeongchang Kim","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5021881378","display_name":"Gary Geunbae Lee","orcid":"https://orcid.org/0000-0002-3692-6732"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gary Geunbae Lee","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100656391"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9035,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.8111727,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"paper 1487","last_page":"Thu1FoP.4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9994000196456909,"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":0.9987000226974487,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/phrase","display_name":"Phrase","score":0.8495632410049438},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7501000165939331},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6393566131591797},{"id":"https://openalex.org/keywords/parsing","display_name":"Parsing","score":0.6389212608337402},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.6074385046958923},{"id":"https://openalex.org/keywords/lexicon","display_name":"Lexicon","score":0.6043022274971008},{"id":"https://openalex.org/keywords/determiner-phrase","display_name":"Determiner phrase","score":0.5865632891654968},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5798014998435974},{"id":"https://openalex.org/keywords/noun-phrase","display_name":"Noun phrase","score":0.5568952560424805},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.48200860619544983},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.45461639761924744},{"id":"https://openalex.org/keywords/rule-based-machine-translation","display_name":"Rule-based machine translation","score":0.42235106229782104},{"id":"https://openalex.org/keywords/phrase-structure-rules","display_name":"Phrase structure rules","score":0.4203493297100067},{"id":"https://openalex.org/keywords/principle-of-maximum-entropy","display_name":"Principle of maximum entropy","score":0.41165703535079956}],"concepts":[{"id":"https://openalex.org/C2776224158","wikidata":"https://www.wikidata.org/wiki/Q187931","display_name":"Phrase","level":2,"score":0.8495632410049438},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7501000165939331},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6393566131591797},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.6389212608337402},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.6074385046958923},{"id":"https://openalex.org/C2778121359","wikidata":"https://www.wikidata.org/wiki/Q8096","display_name":"Lexicon","level":2,"score":0.6043022274971008},{"id":"https://openalex.org/C88880766","wikidata":"https://www.wikidata.org/wiki/Q1201147","display_name":"Determiner phrase","level":4,"score":0.5865632891654968},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5798014998435974},{"id":"https://openalex.org/C153962237","wikidata":"https://www.wikidata.org/wiki/Q1401131","display_name":"Noun phrase","level":3,"score":0.5568952560424805},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.48200860619544983},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.45461639761924744},{"id":"https://openalex.org/C53893814","wikidata":"https://www.wikidata.org/wiki/Q7378909","display_name":"Rule-based machine translation","level":2,"score":0.42235106229782104},{"id":"https://openalex.org/C80877019","wikidata":"https://www.wikidata.org/wiki/Q7188074","display_name":"Phrase structure rules","level":3,"score":0.4203493297100067},{"id":"https://openalex.org/C9679016","wikidata":"https://www.wikidata.org/wiki/Q1417473","display_name":"Principle of maximum entropy","level":2,"score":0.41165703535079956},{"id":"https://openalex.org/C121934690","wikidata":"https://www.wikidata.org/wiki/Q1084","display_name":"Noun","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.21437/interspeech.2006-594","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2006-594","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2006","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W52022909","https://openalex.org/W60337842","https://openalex.org/W78214405","https://openalex.org/W92308982","https://openalex.org/W1599910466","https://openalex.org/W1934019294","https://openalex.org/W1994557139","https://openalex.org/W2025617415","https://openalex.org/W2099227075","https://openalex.org/W2147880316"],"related_works":["https://openalex.org/W4283807455","https://openalex.org/W2152509152","https://openalex.org/W2243938947","https://openalex.org/W2152037873","https://openalex.org/W2912275637","https://openalex.org/W2387191819","https://openalex.org/W2349210087","https://openalex.org/W2040087403","https://openalex.org/W298855569","https://openalex.org/W2955876842"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,36,100],"present":[4],"a":[5,28,55,74],"new":[6],"phrase":[7,21,42,87,111,116],"break":[8,22,112],"prediction":[9,23,40],"method":[10],"that":[11],"integrates":[12],"second-order":[13,79],"information":[14],"into":[15,27],"general":[16],"maximum":[17],"entropy":[18],"model.":[19],"The":[20,34],"problem":[24,30],"was":[25],"mapped":[26],"classification":[29],"in":[31,65,96,108],"our":[32],"research.":[33],"features":[35,51,69,80,91],"used":[37,95],"for":[38],"the":[39,66,97,109],"of":[41,45,58,63,83],"breaks":[43],"are":[44],"several":[46],"layers":[47],"such":[48],"as":[49],"local":[50],"(part-of-speech":[52],"(POS)":[53],"tags,":[54],"lexicon,":[56],"lengths":[57],"eojeols":[59],"1":[60],"and":[61,78,85,94,99],"location":[62],"juncture":[64],"sentence),":[67],"global":[68],"(chunk":[70],"label":[71],"derived":[72],"from":[73],"eojeol":[75],"parse":[76],"tree)":[77],"(distance":[81],"probability":[82],"previous":[84],"next":[86],"break).":[88],"These":[89],"three":[90],"were":[92,101],"combined":[93],"experiments,":[98],"able":[102],"to":[103],"generate":[104],"good":[105],"performance":[106],"especially":[107],"major":[110],"prediction.":[113],"Index":[114],"Terms:":[115],"break,":[117],"prosodic":[118],"phrasing,":[119],"speech":[120],"synthesis,":[121],"ToBI":[122]},"counts_by_year":[{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":3},{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}