{"id":"https://openalex.org/W3115886174","doi":"https://doi.org/10.1109/gcce50665.2020.9291989","title":"Sequence-To-One Neural Networks for Japanese Dialect Speech Classification","display_name":"Sequence-To-One Neural Networks for Japanese Dialect Speech Classification","publication_year":2020,"publication_date":"2020-10-13","ids":{"openalex":"https://openalex.org/W3115886174","doi":"https://doi.org/10.1109/gcce50665.2020.9291989","mag":"3115886174"},"language":"en","primary_location":{"id":"doi:10.1109/gcce50665.2020.9291989","is_oa":false,"landing_page_url":"https://doi.org/10.1109/gcce50665.2020.9291989","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 9th Global Conference on Consumer Electronics (GCCE)","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/A5049831812","display_name":"Ryo Imaizumi","orcid":null},"institutions":[{"id":"https://openalex.org/I69740276","display_name":"Tokyo Metropolitan University","ror":"https://ror.org/00ws30h19","country_code":"JP","type":"education","lineage":["https://openalex.org/I69740276"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Ryo Imaizumi","raw_affiliation_strings":["Tokyo Metropolitan University, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Tokyo Metropolitan University, Tokyo, Japan","institution_ids":["https://openalex.org/I69740276"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060644399","display_name":"Ryo Masumura","orcid":"https://orcid.org/0000-0002-2415-4149"},"institutions":[{"id":"https://openalex.org/I2251713219","display_name":"NTT (Japan)","ror":"https://ror.org/00berct97","country_code":"JP","type":"company","lineage":["https://openalex.org/I2251713219"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ryo Masumura","raw_affiliation_strings":["Nippon Telegraph and Telephone Corporation, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Nippon Telegraph and Telephone Corporation, Tokyo, Japan","institution_ids":["https://openalex.org/I2251713219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067910092","display_name":"Sayaka Shiota","orcid":"https://orcid.org/0000-0002-2364-068X"},"institutions":[{"id":"https://openalex.org/I69740276","display_name":"Tokyo Metropolitan University","ror":"https://ror.org/00ws30h19","country_code":"JP","type":"education","lineage":["https://openalex.org/I69740276"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Sayaka Shiota","raw_affiliation_strings":["Tokyo Metropolitan University, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Tokyo Metropolitan University, Tokyo, Japan","institution_ids":["https://openalex.org/I69740276"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015250468","display_name":"Hitoshi Kiya","orcid":"https://orcid.org/0000-0001-8061-3090"},"institutions":[{"id":"https://openalex.org/I69740276","display_name":"Tokyo Metropolitan University","ror":"https://ror.org/00ws30h19","country_code":"JP","type":"education","lineage":["https://openalex.org/I69740276"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hitoshi Kiya","raw_affiliation_strings":["Tokyo Metropolitan University, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Tokyo Metropolitan University, Tokyo, Japan","institution_ids":["https://openalex.org/I69740276"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5049831812"],"corresponding_institution_ids":["https://openalex.org/I69740276"],"apc_list":null,"apc_paid":null,"fwci":0.2651,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.64981417,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"119","issue":null,"first_page":"933","last_page":"935"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9998000264167786,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9998000264167786,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9997000098228455,"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":0.998199999332428,"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":0.7145817279815674},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6510019302368164},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6372421979904175},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.567783534526825},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4801437556743622},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4709033966064453},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.34314286708831787}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7145817279815674},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6510019302368164},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6372421979904175},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.567783534526825},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4801437556743622},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4709033966064453},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.34314286708831787},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/gcce50665.2020.9291989","is_oa":false,"landing_page_url":"https://doi.org/10.1109/gcce50665.2020.9291989","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 9th Global Conference on Consumer Electronics (GCCE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6299999952316284,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W179875071","https://openalex.org/W2155980578","https://openalex.org/W2160802179","https://openalex.org/W2293634267","https://openalex.org/W2399175133","https://openalex.org/W2470673105","https://openalex.org/W2515090196","https://openalex.org/W2963032538","https://openalex.org/W2996402398","https://openalex.org/W3019239952","https://openalex.org/W6607333740","https://openalex.org/W6696934422","https://openalex.org/W6725861815","https://openalex.org/W6771906277"],"related_works":["https://openalex.org/W2611614995","https://openalex.org/W2386387936","https://openalex.org/W2368651715","https://openalex.org/W2789919619","https://openalex.org/W1552159754","https://openalex.org/W2148757832","https://openalex.org/W2293457016","https://openalex.org/W2131420137","https://openalex.org/W3169305685","https://openalex.org/W3107474891"],"abstract_inverted_index":{"Automatic":[0],"speech":[1,14,46,62,69,84],"recognition":[2],"(ASR)":[3],"is":[4,18,27,36],"usually":[5],"constructed":[6],"for":[7],"recognizing":[8],"standard":[9],"language.":[10],"Thus,":[11],"when":[12],"input":[13],"includes":[15],"dialect":[16,45,61,68],"which":[17],"a":[19,22,44,66,93],"variety":[20],"of":[21,25,54,60,79],"language,":[23],"performance":[24,53],"ASR":[26,40,56],"seriously":[28],"degraded.":[29],"To":[30],"relax":[31],"this":[32,50],"problem,":[33],"an":[34],"approach":[35],"to":[37],"use":[38],"dialect-specific":[39,55],"recognizers":[41],"by":[42],"introducing":[43],"classification":[47,70,85,94,98],"module.":[48],"In":[49],"situation,":[51],"the":[52,80],"depends":[57],"on":[58],"that":[59,76,92],"classification.":[63],"We":[64],"propose":[65],"Japanese":[67],"method":[71],"using":[72],"sequence-to-one":[73],"neural":[74],"networks":[75],"are":[77],"one":[78],"successful":[81],"methods":[82],"in":[83],"research":[86],"fields.":[87],"The":[88],"experimental":[89],"results":[90],"showed":[91],"system":[95],"provided":[96],"high":[97],"accuracy.":[99]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
