{"id":"https://openalex.org/W3011985699","doi":"https://doi.org/10.1109/apsipaasc47483.2019.9023098","title":"Speech Emotion Recognition Using Speech Feature and Word Embedding","display_name":"Speech Emotion Recognition Using Speech Feature and Word Embedding","publication_year":2019,"publication_date":"2019-11-01","ids":{"openalex":"https://openalex.org/W3011985699","doi":"https://doi.org/10.1109/apsipaasc47483.2019.9023098","mag":"3011985699"},"language":"en","primary_location":{"id":"doi:10.1109/apsipaasc47483.2019.9023098","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipaasc47483.2019.9023098","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","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/A5065879041","display_name":"Bagus Tris Atmaja","orcid":"https://orcid.org/0000-0003-1560-2824"},"institutions":[{"id":"https://openalex.org/I177738480","display_name":"Japan Advanced Institute of Science and Technology","ror":"https://ror.org/03frj4r98","country_code":"JP","type":"education","lineage":["https://openalex.org/I177738480"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Bagus Tris Atmaja","raw_affiliation_strings":["Japan Advanced Institute of Science and Technology, Nomi, Japan"],"affiliations":[{"raw_affiliation_string":"Japan Advanced Institute of Science and Technology, Nomi, Japan","institution_ids":["https://openalex.org/I177738480"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107485330","display_name":"Kiyoaki Shirai","orcid":null},"institutions":[{"id":"https://openalex.org/I177738480","display_name":"Japan Advanced Institute of Science and Technology","ror":"https://ror.org/03frj4r98","country_code":"JP","type":"education","lineage":["https://openalex.org/I177738480"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kiyoaki Shirai","raw_affiliation_strings":["Japan Advanced Institute of Science and Technology, Nomi, Japan"],"affiliations":[{"raw_affiliation_string":"Japan Advanced Institute of Science and Technology, Nomi, Japan","institution_ids":["https://openalex.org/I177738480"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055059119","display_name":"Masato Akagi","orcid":"https://orcid.org/0000-0003-2450-6754"},"institutions":[{"id":"https://openalex.org/I177738480","display_name":"Japan Advanced Institute of Science and Technology","ror":"https://ror.org/03frj4r98","country_code":"JP","type":"education","lineage":["https://openalex.org/I177738480"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masato Akagi","raw_affiliation_strings":["Japan Advanced Institute of Science and Technology, Nomi, Japan"],"affiliations":[{"raw_affiliation_string":"Japan Advanced Institute of Science and Technology, Nomi, Japan","institution_ids":["https://openalex.org/I177738480"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5065879041"],"corresponding_institution_ids":["https://openalex.org/I177738480"],"apc_list":null,"apc_paid":null,"fwci":3.0445,"has_fulltext":false,"cited_by_count":41,"citation_normalized_percentile":{"value":0.91603053,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"519","last_page":"523"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9998999834060669,"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"}},{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9988999962806702,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9968000054359436,"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/speech-recognition","display_name":"Speech recognition","score":0.7839479446411133},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7592283487319946},{"id":"https://openalex.org/keywords/utterance","display_name":"Utterance","score":0.6393939852714539},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6132320165634155},{"id":"https://openalex.org/keywords/emotion-recognition","display_name":"Emotion recognition","score":0.5786344408988953},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.5164340138435364},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.498917818069458},{"id":"https://openalex.org/keywords/word-embedding","display_name":"Word embedding","score":0.46481427550315857},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.4464940130710602},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.41867369413375854},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4123408794403076},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3706880211830139},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0822526216506958},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.0639573335647583}],"concepts":[{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.7839479446411133},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7592283487319946},{"id":"https://openalex.org/C2775852435","wikidata":"https://www.wikidata.org/wiki/Q258403","display_name":"Utterance","level":2,"score":0.6393939852714539},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6132320165634155},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.5786344408988953},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5164340138435364},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.498917818069458},{"id":"https://openalex.org/C2777462759","wikidata":"https://www.wikidata.org/wiki/Q18395344","display_name":"Word embedding","level":3,"score":0.46481427550315857},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.4464940130710602},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.41867369413375854},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4123408794403076},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3706880211830139},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0822526216506958},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0639573335647583},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/apsipaasc47483.2019.9023098","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipaasc47483.2019.9023098","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","raw_type":"proceedings-article"},{"id":"pmh:oai:dspace.jaist.ac.jp:10119/16657","is_oa":false,"landing_page_url":"http://hdl.handle.net/10119/16657","pdf_url":null,"source":{"id":"https://openalex.org/S4406922663","display_name":"JAIST Repository","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":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":""}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W141482854","https://openalex.org/W1534131679","https://openalex.org/W1569087642","https://openalex.org/W2103018059","https://openalex.org/W2133564696","https://openalex.org/W2146334809","https://openalex.org/W2212703438","https://openalex.org/W2250539671","https://openalex.org/W2583743457","https://openalex.org/W2602034649","https://openalex.org/W2607071059","https://openalex.org/W2750499125","https://openalex.org/W2755760886","https://openalex.org/W2889169802","https://openalex.org/W2889191349","https://openalex.org/W2962736520","https://openalex.org/W2962770129","https://openalex.org/W2963266340","https://openalex.org/W2964308564","https://openalex.org/W3158775612","https://openalex.org/W4299280181","https://openalex.org/W6633893584","https://openalex.org/W6744573199"],"related_works":["https://openalex.org/W2529301793","https://openalex.org/W2384121599","https://openalex.org/W2038083449","https://openalex.org/W3177678247","https://openalex.org/W1999617572","https://openalex.org/W2944572343","https://openalex.org/W2333799855","https://openalex.org/W2351687372","https://openalex.org/W2004087835","https://openalex.org/W4286432911"],"abstract_inverted_index":{"Emotion":[0],"recognition":[1,16,34,76,152],"can":[2,25,39],"be":[3,26,40],"performed":[4],"automatically":[5],"from":[6,42],"many":[7],"modalities.":[8,172],"This":[9,155],"paper":[10],"presents":[11],"a":[12,78],"categorical":[13],"speech":[14,18,29,47,134,144],"emotion":[15,33,63,75,105,126,151],"using":[17,165],"feature":[19,58,72],"and":[20,36,77,97,135],"word":[21],"embedding.":[22],"Text":[23],"features":[24,30,38,82],"combined":[27],"with":[28,146,153],"to":[31,120,143],"improve":[32],"accuracy,":[35],"both":[37,81],"obtained":[41],"speech.":[43],"Here,":[44],"we":[45],"use":[46],"segments,":[48],"by":[49,112,163],"removing":[50],"silences":[51],"in":[52,116],"an":[53,70],"utterance,":[54],"where":[55],"the":[56,131,159,166,170],"acoustic":[57,104],"is":[59,67,83],"extracted":[60],"for":[61,73,85,95,103],"speech-based":[62],"recognition.":[64,106],"Word":[65],"embedding":[66],"used":[68,94],"as":[69],"input":[71],"text":[74,96,136,149],"combination":[79,132],"of":[80,123,133],"proposed":[84,161],"performance":[86],"improvement":[87],"purpose.":[88],"Two":[89],"unidirectional":[90],"LSTM":[91],"layers":[92,100],"are":[93,101,110],"fully":[98,113],"connected":[99,114],"applied":[102],"Both":[107],"networks":[108,115],"then":[109],"merged":[111],"early":[117],"fusion":[118],"way":[119],"produce":[121],"one":[122],"four":[124],"predicted":[125],"categories.":[127],"The":[128],"result":[129,156],"shows":[130],"achieve":[137],"higher":[138],"accuracy":[139],"i.e.":[140],"75.49%":[141],"compared":[142],"only":[145,150],"58.29%":[147],"or":[148],"68.01%.":[154],"also":[157],"outperforms":[158],"previously":[160],"methods":[162],"others":[164],"same":[167,171],"dataset":[168],"on":[169]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":5}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}