{"id":"https://openalex.org/W4317419706","doi":"https://doi.org/10.1109/gcce56475.2022.10014285","title":"Multi-condition Training and System Combination for Automatic MOS Prediction","display_name":"Multi-condition Training and System Combination for Automatic MOS Prediction","publication_year":2022,"publication_date":"2022-10-18","ids":{"openalex":"https://openalex.org/W4317419706","doi":"https://doi.org/10.1109/gcce56475.2022.10014285"},"language":"en","primary_location":{"id":"doi:10.1109/gcce56475.2022.10014285","is_oa":false,"landing_page_url":"https://doi.org/10.1109/gcce56475.2022.10014285","pdf_url":null,"source":{"id":"https://openalex.org/S4363607800","display_name":"2022 IEEE 11th Global Conference on Consumer Electronics (GCCE)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 11th 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/A5022767796","display_name":"Yuuki Tachioka","orcid":"https://orcid.org/0009-0002-0587-2943"},"institutions":[{"id":"https://openalex.org/I4210132650","display_name":"Denso (Japan)","ror":"https://ror.org/04hkpfa76","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210132650"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Yuuki Tachioka","raw_affiliation_strings":["Denso IT Laboratory,Tokyo,Japan","Denso IT Laboratory, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Denso IT Laboratory,Tokyo,Japan","institution_ids":["https://openalex.org/I4210132650"]},{"raw_affiliation_string":"Denso IT Laboratory, Tokyo, Japan","institution_ids":["https://openalex.org/I4210132650"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5022767796"],"corresponding_institution_ids":["https://openalex.org/I4210132650"],"apc_list":null,"apc_paid":null,"fwci":0.1039,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.34938591,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"346","last_page":"347"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","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"}},"topics":[{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","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/T12031","display_name":"Speech and dialogue systems","score":0.9919000267982483,"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/T10860","display_name":"Speech and Audio Processing","score":0.9901999831199646,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.767749547958374},{"id":"https://openalex.org/keywords/mean-opinion-score","display_name":"Mean opinion score","score":0.7631248235702515},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6005702018737793},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.5713749527931213},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.5558531880378723},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49960899353027344},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.484625905752182},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4636211693286896},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.46145686507225037},{"id":"https://openalex.org/keywords/task-analysis","display_name":"Task analysis","score":0.4305955469608307},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4199192523956299},{"id":"https://openalex.org/keywords/performance-prediction","display_name":"Performance prediction","score":0.4188763499259949},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.17071852087974548},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12262126803398132}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.767749547958374},{"id":"https://openalex.org/C62897895","wikidata":"https://www.wikidata.org/wiki/Q1915482","display_name":"Mean opinion score","level":3,"score":0.7631248235702515},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6005702018737793},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.5713749527931213},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.5558531880378723},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49960899353027344},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.484625905752182},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4636211693286896},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.46145686507225037},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.4305955469608307},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4199192523956299},{"id":"https://openalex.org/C2777115002","wikidata":"https://www.wikidata.org/wiki/Q7168246","display_name":"Performance prediction","level":2,"score":0.4188763499259949},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.17071852087974548},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12262126803398132},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/gcce56475.2022.10014285","is_oa":false,"landing_page_url":"https://doi.org/10.1109/gcce56475.2022.10014285","pdf_url":null,"source":{"id":"https://openalex.org/S4363607800","display_name":"2022 IEEE 11th Global Conference on Consumer Electronics (GCCE)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 11th Global Conference on Consumer Electronics (GCCE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.550000011920929}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W3036601975","https://openalex.org/W3202278141","https://openalex.org/W3207932315","https://openalex.org/W4296068974","https://openalex.org/W6780218876"],"related_works":["https://openalex.org/W3125011624","https://openalex.org/W1508631387","https://openalex.org/W2370917603","https://openalex.org/W2017776670","https://openalex.org/W2952760143","https://openalex.org/W2347897961","https://openalex.org/W2979236518","https://openalex.org/W2358318464","https://openalex.org/W4287630611","https://openalex.org/W3094960827"],"abstract_inverted_index":{"The":[0,36,66],"quality":[1],"of":[2,51,110],"text-to-speech":[3],"synthesis":[4],"and":[5,60,70],"voice":[6,61],"conversion":[7,62],"has":[8,68],"been":[9],"improved.":[10],"To":[11,88],"evaluate":[12],"their":[13],"quality,":[14],"the":[15,49,56,85,102,107,119],"mean":[16],"opinion":[17],"score":[18],"(MOS)":[19],"is":[20,39,64],"widely":[21],"used":[22],"but":[23],"its":[24],"scoring":[25],"requires":[26],"human":[27],"evaluation.":[28],"Automatic":[29],"MOS":[30,45,50,78,103,111],"prediction":[31,46,79,104,112],"can":[32],"reduce":[33],"development":[34],"costs.":[35],"VoiceMOS":[37],"challenge":[38,63,67],"a":[40],"shared":[41],"task":[42],"for":[43,84],"automatic":[44,77],"in":[47],"which":[48],"synthesized":[52],"speech":[53],"taken":[54],"from":[55,123],"previous":[57],"Blizzard":[58],"challenges":[59],"predicted.":[65],"main":[69],"out-of-domain":[71],"(ood)":[72],"tracks;":[73],"we":[74,91],"found":[75],"that":[76,97,115],"systems":[80],"show":[81,96],"poor":[82],"performance":[83],"ood":[86],"track.":[87],"improve":[89],"this,":[90],"introduce":[92],"multi-condition":[93,98,116],"training.":[94],"Experiments":[95],"training":[99,117],"significantly":[100],"improved":[101],"performance.":[105],"Visualizing":[106],"embedded":[108],"vectors":[109],"models":[113],"shows":[114],"increased":[118],"margin":[120],"between":[121],"samples":[122],"two":[124],"tracks.":[125]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}