{"id":"https://openalex.org/W2593817868","doi":"https://doi.org/10.1109/robio.2016.7866449","title":"Laughing voice recognition using periodic waveforms and voice-likeness features","display_name":"Laughing voice recognition using periodic waveforms and voice-likeness features","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2593817868","doi":"https://doi.org/10.1109/robio.2016.7866449","mag":"2593817868"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/robio.2016.7866449","pdf_url":null,"source":{"id":"https://openalex.org/S4363607846","display_name":"2021 IEEE International Conference on Robotics and Biomimetics (ROBIO)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5041561769","display_name":"Taisuke Sakano","orcid":null},"institutions":[{"id":"https://openalex.org/I161296585","display_name":"Tokyo University of Science","ror":"https://ror.org/05sj3n476","country_code":"JP","type":"education","lineage":["https://openalex.org/I161296585"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Taisuke Sakano","raw_affiliation_strings":["Tokyo University of Science, Chiba, Japan"],"affiliations":[{"raw_affiliation_string":"Tokyo University of Science, Chiba, Japan","institution_ids":["https://openalex.org/I161296585"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104387827","display_name":"Takahiro Kigawa","orcid":null},"institutions":[{"id":"https://openalex.org/I161296585","display_name":"Tokyo University of Science","ror":"https://ror.org/05sj3n476","country_code":"JP","type":"education","lineage":["https://openalex.org/I161296585"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takahiro Kigawa","raw_affiliation_strings":["Tokyo University of Science, Chiba, Japan"],"affiliations":[{"raw_affiliation_string":"Tokyo University of Science, Chiba, Japan","institution_ids":["https://openalex.org/I161296585"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056733127","display_name":"Masanori Sugimoto","orcid":"https://orcid.org/0000-0002-3781-0539"},"institutions":[{"id":"https://openalex.org/I205349734","display_name":"Hokkaido University","ror":"https://ror.org/02e16g702","country_code":"JP","type":"funder","lineage":["https://openalex.org/I205349734"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masanori Sugimoto","raw_affiliation_strings":["Hokkaido University, Hokkaido, Japan"],"affiliations":[{"raw_affiliation_string":"Hokkaido University, Hokkaido, Japan","institution_ids":["https://openalex.org/I205349734"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076253930","display_name":"Fusako Kusunoki","orcid":"https://orcid.org/0009-0005-1810-6115"},"institutions":[{"id":"https://openalex.org/I170148708","display_name":"Tama Art University","ror":"https://ror.org/01044vd48","country_code":"JP","type":"education","lineage":["https://openalex.org/I170148708"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Fusako Kusunoki","raw_affiliation_strings":["Tama Art University, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Tama Art University, Tokyo, Japan","institution_ids":["https://openalex.org/I170148708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110608131","display_name":"Shigenori Inagaki","orcid":null},"institutions":[{"id":"https://openalex.org/I65837984","display_name":"Kobe University","ror":"https://ror.org/03tgsfw79","country_code":"JP","type":"funder","lineage":["https://openalex.org/I65837984"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shigenori Inagaki","raw_affiliation_strings":["Kobe University, Kobe, Japan"],"affiliations":[{"raw_affiliation_string":"Kobe University, Kobe, Japan","institution_ids":["https://openalex.org/I65837984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057754307","display_name":"Hiroshi Mizoguchi","orcid":"https://orcid.org/0000-0002-1322-6098"},"institutions":[{"id":"https://openalex.org/I161296585","display_name":"Tokyo University of Science","ror":"https://ror.org/05sj3n476","country_code":"JP","type":"education","lineage":["https://openalex.org/I161296585"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hiroshi Mizoguchi","raw_affiliation_strings":["Tokyo University of Science, Chiba, Japan"],"affiliations":[{"raw_affiliation_string":"Tokyo University of Science, Chiba, Japan","institution_ids":["https://openalex.org/I161296585"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"fulltext_origin":"ngrams","cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":66},"biblio":{"volume":null,"issue":null,"first_page":"964","last_page":"969"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9986,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10860","display_name":"Speech and Audio Processing","score":0.9986,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.9938,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9761,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/feature","display_name":"Feature (linguistics)","score":0.60172015},{"id":"https://openalex.org/keywords/human-voice","display_name":"Human voice","score":0.5783479},{"id":"https://openalex.org/keywords/voice-analysis","display_name":"Voice analysis","score":0.50425184}],"concepts":[{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.81349635},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6756369},{"id":"https://openalex.org/C197424946","wikidata":"https://www.wikidata.org/wiki/Q1165717","display_name":"Waveform","level":3,"score":0.6216353},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.60172015},{"id":"https://openalex.org/C20766975","wikidata":"https://www.wikidata.org/wiki/Q7390","display_name":"Human voice","level":2,"score":0.5783479},{"id":"https://openalex.org/C133892786","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker recognition","level":2,"score":0.5449175},{"id":"https://openalex.org/C182964821","wikidata":"https://www.wikidata.org/wiki/Q7939498","display_name":"Voice analysis","level":2,"score":0.50425184},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.41668028},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4122034},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35101944},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.07344419},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/robio.2016.7866449","pdf_url":null,"source":{"id":"https://openalex.org/S4363607846","display_name":"2021 IEEE International Conference on Robotics and Biomimetics (ROBIO)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":9,"referenced_works":["https://openalex.org/W194042399","https://openalex.org/W1994306882","https://openalex.org/W2043352683","https://openalex.org/W2058276039","https://openalex.org/W2069636541","https://openalex.org/W210863884","https://openalex.org/W2116546045","https://openalex.org/W2158143121","https://openalex.org/W2164780916"],"related_works":["https://openalex.org/W4399374970","https://openalex.org/W3144640894","https://openalex.org/W2617085266","https://openalex.org/W25843091","https://openalex.org/W2072764920","https://openalex.org/W2036663051","https://openalex.org/W1973693762","https://openalex.org/W1945860337","https://openalex.org/W1560125148","https://openalex.org/W104892710"],"abstract_inverted_index":{"With":[0],"a":[1,9,13,21,59,66,73,108],"goal":[2],"of":[3,33,86,112],"advancing":[4],"human-machine":[5],"collaboration,":[6],"we":[7,57,71,92,99],"propose":[8,58],"method":[10,25,63,129],"to":[11,102],"recognize":[12,104],"laughing":[14,22,35,39,60,74,88,105,137],"voice.":[15,36,138],"A":[16],"previous":[17,118],"study":[18],"that":[19,64],"proposed":[20,80,128],"voice":[23,61,75,89,106],"recognition":[24,62,76,90,121],"was":[26],"based":[27],"on":[28],"the":[29,34,84,87,117,120],"periodic":[30],"waveform":[31],"feature":[32],"However,":[37],"identifying":[38],"voices":[40],"from":[41],"waveforms":[42],"is":[43],"problematic,":[44],"because":[45],"this":[46,55,94],"can":[47,130],"result":[48],"in":[49,135],"false":[50],"positive":[51],"results.":[52],"To":[53,82],"overcome":[54],"problem,":[56],"incorporates":[65],"voice-likeness":[67],"feature.":[68],"In":[69,96,114],"addition,":[70],"make":[72],"system":[77],"using":[78],"our":[79,97,127],"method.":[81],"confirm":[83],"efficacy":[85],"method,":[91],"evaluated":[93],"system.":[95],"evaluation,":[98],"were":[100],"able":[101],"correctly":[103],"at":[107],"high":[109],"success":[110],"rate":[111,122],"97%.":[113],"comparison":[115],"with":[116],"study,":[119],"improved":[123],"by":[124],"18%;":[125],"therefore,":[126],"be":[131],"considered":[132],"an":[133],"effective":[134],"recognizing":[136]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2593817868","counts_by_year":[],"updated_date":"2025-01-28T13:52:31.640038","created_date":"2017-03-16"}