{"id":"https://openalex.org/W2250613158","doi":"https://doi.org/10.3115/v1/d14-1091","title":"Syllable weight encodes mostly the same information for English word segmentation as dictionary stress","display_name":"Syllable weight encodes mostly the same information for English word segmentation as dictionary stress","publication_year":2014,"publication_date":"2014-01-01","ids":{"openalex":"https://openalex.org/W2250613158","doi":"https://doi.org/10.3115/v1/d14-1091","mag":"2250613158"},"language":"en","primary_location":{"id":"doi:10.3115/v1/d14-1091","is_oa":true,"landing_page_url":"https://doi.org/10.3115/v1/d14-1091","pdf_url":"https://aclanthology.org/D14-1091.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/D14-1091.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5081404974","display_name":"John K. Pate","orcid":null},"institutions":[{"id":"https://openalex.org/I99043593","display_name":"Macquarie University","ror":"https://ror.org/01sf06y89","country_code":"AU","type":"education","lineage":["https://openalex.org/I99043593"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"John K Pate","raw_affiliation_strings":["Centre for Language Technology Macquarie University Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"Centre for Language Technology Macquarie University Sydney, NSW, Australia","institution_ids":["https://openalex.org/I99043593"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034461489","display_name":"Mark Johnson","orcid":"https://orcid.org/0000-0003-4809-8441"},"institutions":[{"id":"https://openalex.org/I99043593","display_name":"Macquarie University","ror":"https://ror.org/01sf06y89","country_code":"AU","type":"education","lineage":["https://openalex.org/I99043593"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Mark Johnson","raw_affiliation_strings":["Centre for Language Technology Macquarie University Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"Centre for Language Technology Macquarie University Sydney, NSW, Australia","institution_ids":["https://openalex.org/I99043593"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5081404974"],"corresponding_institution_ids":["https://openalex.org/I99043593"],"apc_list":null,"apc_paid":null,"fwci":0.8714,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.78790572,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"844","last_page":"853"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10730","display_name":"Language Development and Disorders","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/3204","display_name":"Developmental and Educational Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10730","display_name":"Language Development and Disorders","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/3204","display_name":"Developmental and Educational Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9976999759674072,"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":0.9973000288009644,"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/syllable","display_name":"Syllable","score":0.7935360670089722},{"id":"https://openalex.org/keywords/stress","display_name":"Stress (linguistics)","score":0.7762529253959656},{"id":"https://openalex.org/keywords/text-segmentation","display_name":"Text segmentation","score":0.7444125413894653},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7209898829460144},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7087737321853638},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.6285098195075989},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6144143342971802},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5728763341903687},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5470857620239258},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.221346914768219}],"concepts":[{"id":"https://openalex.org/C109089402","wikidata":"https://www.wikidata.org/wiki/Q8188","display_name":"Syllable","level":2,"score":0.7935360670089722},{"id":"https://openalex.org/C21036866","wikidata":"https://www.wikidata.org/wiki/Q181767","display_name":"Stress (linguistics)","level":2,"score":0.7762529253959656},{"id":"https://openalex.org/C98501671","wikidata":"https://www.wikidata.org/wiki/Q1948408","display_name":"Text segmentation","level":3,"score":0.7444125413894653},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7209898829460144},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7087737321853638},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.6285098195075989},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6144143342971802},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5728763341903687},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5470857620239258},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.221346914768219},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3115/v1/d14-1091","is_oa":true,"landing_page_url":"https://doi.org/10.3115/v1/d14-1091","pdf_url":"https://aclanthology.org/D14-1091.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.683.1907","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.683.1907","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://emnlp2014.org/papers/pdf/EMNLP2014091.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.696.3500","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.696.3500","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://aclweb.org/anthology/D/D14/D14-1091.pdf","raw_type":"text"}],"best_oa_location":{"id":"doi:10.3115/v1/d14-1091","is_oa":true,"landing_page_url":"https://doi.org/10.3115/v1/d14-1091","pdf_url":"https://aclanthology.org/D14-1091.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.75,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2250613158.pdf","grobid_xml":"https://content.openalex.org/works/W2250613158.grobid-xml"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W18218877","https://openalex.org/W32086369","https://openalex.org/W150776213","https://openalex.org/W1563026167","https://openalex.org/W1986595082","https://openalex.org/W2029948425","https://openalex.org/W2036572838","https://openalex.org/W2059824090","https://openalex.org/W2074546930","https://openalex.org/W2098717046","https://openalex.org/W2114326974","https://openalex.org/W2117126688","https://openalex.org/W2124973255","https://openalex.org/W2125814841","https://openalex.org/W2126377586","https://openalex.org/W2126449874","https://openalex.org/W2142111485","https://openalex.org/W2144800021","https://openalex.org/W2148279902","https://openalex.org/W2166391802","https://openalex.org/W2226889031","https://openalex.org/W2952343510","https://openalex.org/W4239549861","https://openalex.org/W4240130228"],"related_works":["https://openalex.org/W2514064218","https://openalex.org/W2094188777","https://openalex.org/W2132658536","https://openalex.org/W2112609279","https://openalex.org/W1581825163","https://openalex.org/W1483316057","https://openalex.org/W2366310385","https://openalex.org/W2399404538","https://openalex.org/W2061937230","https://openalex.org/W2978383222"],"abstract_inverted_index":{"Stress":[0],"is":[1,48],"a":[2,21,43,96],"useful":[3],"cue":[4,97],"for":[5,112],"English":[6,116],"word":[7,76,99,113],"segmentation.":[8],"A":[9],"wide":[10],"range":[11],"of":[12,31,92],"computational":[13],"models":[14,78],"have":[15],"found":[16],"that":[17,36,79,104,117],"stress":[18,41,47,69,120],"cues":[19],"enable":[20],"2-10%":[22],"improvement":[23],"in":[24,55,70,115],"segmentation":[25,77,114],"accuracy,":[26],"depending":[27],"on":[28],"the":[29,90,109],"kind":[30],"model,":[32],"by":[33],"using":[34,42],"input":[35],"has":[37],"been":[38],"annotated":[39,118],"with":[40,62],"pronouncing":[44],"dictionary.":[45],"However,":[46],"neither":[49],"invariably":[50],"produced":[51],"nor":[52],"unambiguously":[53],"identifiable":[54],"real":[56],"speech.":[57],"Heavy":[58],"syllables,":[59],"i.e.":[60],"those":[61],"long":[63],"vowels":[64],"or":[65,83,86],"syllable":[66,84,93,105],"codas,":[67],"attract":[68],"English.":[71],"We":[72],"devise":[73],"Adaptor":[74],"Grammar":[75],"exploit":[80],"either":[81],"stress,":[82],"weight,":[85],"both,":[87],"and":[88],"evaluate":[89],"utility":[91],"weight":[94,106],"as":[95],"to":[98],"boundaries.":[100],"Our":[101],"results":[102],"suggest":[103],"encodes":[107],"largely":[108],"same":[110],"information":[111],"dictionary":[119],"does.":[121]},"counts_by_year":[{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}