{"id":"https://openalex.org/W3210029122","doi":"https://doi.org/10.3390/s21217111","title":"An Empathy Evaluation System Using Spectrogram Image Features of Audio","display_name":"An Empathy Evaluation System Using Spectrogram Image Features of Audio","publication_year":2021,"publication_date":"2021-10-26","ids":{"openalex":"https://openalex.org/W3210029122","doi":"https://doi.org/10.3390/s21217111","mag":"3210029122","pmid":"https://pubmed.ncbi.nlm.nih.gov/34770419"},"language":"en","primary_location":{"id":"doi:10.3390/s21217111","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21217111","pdf_url":"https://www.mdpi.com/1424-8220/21/21/7111/pdf?version=1635911013","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/21/21/7111/pdf?version=1635911013","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5066905801","display_name":"Jing Zhang","orcid":"https://orcid.org/0000-0002-5230-6285"},"institutions":[{"id":"https://openalex.org/I157264075","display_name":"Sangmyung University","ror":"https://ror.org/01x4whx42","country_code":"KR","type":"education","lineage":["https://openalex.org/I157264075"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jing Zhang","raw_affiliation_strings":["Department of Emotion Engineering, University of Sangmyung, Seoul 03016, Korea"],"raw_orcid":"https://orcid.org/0000-0002-5230-6285","affiliations":[{"raw_affiliation_string":"Department of Emotion Engineering, University of Sangmyung, Seoul 03016, Korea","institution_ids":["https://openalex.org/I157264075"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075762409","display_name":"Xingyu Wen","orcid":"https://orcid.org/0000-0002-1731-5178"},"institutions":[{"id":"https://openalex.org/I157264075","display_name":"Sangmyung University","ror":"https://ror.org/01x4whx42","country_code":"KR","type":"education","lineage":["https://openalex.org/I157264075"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Xingyu Wen","raw_affiliation_strings":["Department of Emotion Engineering, University of Sangmyung, Seoul 03016, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Emotion Engineering, University of Sangmyung, Seoul 03016, Korea","institution_ids":["https://openalex.org/I157264075"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025837786","display_name":"Ayoung Cho","orcid":"https://orcid.org/0000-0003-0035-3853"},"institutions":[{"id":"https://openalex.org/I157264075","display_name":"Sangmyung University","ror":"https://ror.org/01x4whx42","country_code":"KR","type":"education","lineage":["https://openalex.org/I157264075"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Ayoung Cho","raw_affiliation_strings":["Department of Emotion Engineering, University of Sangmyung, Seoul 03016, Korea"],"raw_orcid":"https://orcid.org/0000-0003-0035-3853","affiliations":[{"raw_affiliation_string":"Department of Emotion Engineering, University of Sangmyung, Seoul 03016, Korea","institution_ids":["https://openalex.org/I157264075"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083471750","display_name":"Mincheol Whang","orcid":"https://orcid.org/0000-0003-4301-9089"},"institutions":[{"id":"https://openalex.org/I157264075","display_name":"Sangmyung University","ror":"https://ror.org/01x4whx42","country_code":"KR","type":"education","lineage":["https://openalex.org/I157264075"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Mincheol Whang","raw_affiliation_strings":["Department of Human Centered Artificial Intelligence, University of Sangmyung, Seoul 03016, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Human Centered Artificial Intelligence, University of Sangmyung, Seoul 03016, Korea","institution_ids":["https://openalex.org/I157264075"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5083471750"],"corresponding_institution_ids":["https://openalex.org/I157264075"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":0.4631,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.62755341,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"21","issue":"21","first_page":"7111","last_page":"7111"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9995999932289124,"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/T11309","display_name":"Music and Audio Processing","score":0.9995999932289124,"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/T10860","display_name":"Speech and Audio Processing","score":0.9509000182151794,"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/T12032","display_name":"Multisensory perception and integration","score":0.9487000107765198,"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/spectrogram","display_name":"Spectrogram","score":0.7166589498519897},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.689123809337616},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.5011208057403564},{"id":"https://openalex.org/keywords/mel-frequency-cepstrum","display_name":"Mel-frequency cepstrum","score":0.48786401748657227},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4794532358646393},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4652332663536072},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.44512906670570374},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.43828338384628296},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.42757248878479004},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4210956394672394},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.41066673398017883},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.322790265083313},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12619447708129883},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.11897599697113037}],"concepts":[{"id":"https://openalex.org/C45273575","wikidata":"https://www.wikidata.org/wiki/Q578970","display_name":"Spectrogram","level":2,"score":0.7166589498519897},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.689123809337616},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.5011208057403564},{"id":"https://openalex.org/C151989614","wikidata":"https://www.wikidata.org/wiki/Q440370","display_name":"Mel-frequency cepstrum","level":3,"score":0.48786401748657227},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4794532358646393},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4652332663536072},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.44512906670570374},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.43828338384628296},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.42757248878479004},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4210956394672394},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.41066673398017883},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.322790265083313},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12619447708129883},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.11897599697113037},{"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},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D004644","descriptor_name":"Emotions","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D004644","descriptor_name":"Emotions","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D004644","descriptor_name":"Emotions","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D004645","descriptor_name":"Empathy","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D004645","descriptor_name":"Empathy","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D004645","descriptor_name":"Empathy","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D009146","descriptor_name":"Music","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D009146","descriptor_name":"Music","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D009146","descriptor_name":"Music","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":5,"locations":[{"id":"doi:10.3390/s21217111","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21217111","pdf_url":"https://www.mdpi.com/1424-8220/21/21/7111/pdf?version=1635911013","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:34770419","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34770419","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:fa39bda1ee17427dbfc19654d63e688c","is_oa":true,"landing_page_url":"https://doaj.org/article/fa39bda1ee17427dbfc19654d63e688c","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 21, Iss 21, p 7111 (2021)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/21/21/7111/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s21217111","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors; Volume 21; Issue 21; Pages: 7111","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:8587789","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8587789","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s21217111","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21217111","pdf_url":"https://www.mdpi.com/1424-8220/21/21/7111/pdf?version=1635911013","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4811031216","display_name":null,"funder_award_id":"NRF-2020R1A2B5B02002770","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G4876659138","display_name":null,"funder_award_id":"2020R1A2B5B02002770","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"},{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3210029122.pdf","grobid_xml":"https://content.openalex.org/works/W3210029122.grobid-xml"},"referenced_works_count":45,"referenced_works":["https://openalex.org/W2385545","https://openalex.org/W254374498","https://openalex.org/W1488076490","https://openalex.org/W1605844890","https://openalex.org/W1983822098","https://openalex.org/W2036723342","https://openalex.org/W2055911634","https://openalex.org/W2066496894","https://openalex.org/W2073716350","https://openalex.org/W2075710390","https://openalex.org/W2087618018","https://openalex.org/W2088335634","https://openalex.org/W2090431713","https://openalex.org/W2091425152","https://openalex.org/W2117170968","https://openalex.org/W2133824856","https://openalex.org/W2144226085","https://openalex.org/W2148600927","https://openalex.org/W2578895956","https://openalex.org/W2623689520","https://openalex.org/W2763524503","https://openalex.org/W2767140395","https://openalex.org/W2786121637","https://openalex.org/W2795078582","https://openalex.org/W2906880328","https://openalex.org/W2911253733","https://openalex.org/W2921936888","https://openalex.org/W2940714935","https://openalex.org/W2950812798","https://openalex.org/W2955717168","https://openalex.org/W2991078974","https://openalex.org/W3001587372","https://openalex.org/W3001983419","https://openalex.org/W3029332980","https://openalex.org/W3048316625","https://openalex.org/W3085570398","https://openalex.org/W3108681799","https://openalex.org/W3121581935","https://openalex.org/W4234099616","https://openalex.org/W4237225249","https://openalex.org/W4239944110","https://openalex.org/W6629033770","https://openalex.org/W6681403236","https://openalex.org/W6780213047","https://openalex.org/W6782695924"],"related_works":["https://openalex.org/W2530685530","https://openalex.org/W4375868962","https://openalex.org/W2011227383","https://openalex.org/W4317383455","https://openalex.org/W2548511587","https://openalex.org/W4293232884","https://openalex.org/W2422472940","https://openalex.org/W2019475500","https://openalex.org/W2548162870","https://openalex.org/W2138847091"],"abstract_inverted_index":{"Watching":[0],"videos":[1,13,45],"online":[2],"has":[3,14,280],"become":[4],"part":[5],"of":[6,54,61,88,92,153,175,181,194,201,248,274,278],"a":[7,15,178,254],"relaxed":[8,29],"lifestyle.":[9],"The":[10,59,127,161,199],"music":[11,55,68,77],"in":[12,70,110,158,215],"sensitive":[16],"influence":[17],"on":[18],"human":[19,263,286],"emotions,":[20],"perception,":[21],"and":[22,32,56,74,94,143,177,212,226,235],"imaginations,":[23],"which":[24,183],"can":[25,184,204],"make":[26,43,80],"people":[27,41,81],"feel":[28],"or":[30],"sad,":[31],"so":[33],"on.":[34],"Therefore,":[35],"it":[36,230],"is":[37,64,133,147,163,168,218,231,259],"particularly":[38],"important":[39,239],"for":[40,241],"who":[42],"advertising":[44,72],"to":[46,65,98,119,123,135,149,221,261,284],"understand":[47],"the":[48,51,67,76,89,100,107,111,137,144,151,165,171,191,210,216,224,246,249,267,272,281],"relationship":[49],"between":[50],"physical":[52],"elements":[53],"empathy":[57,156],"characteristics.":[58],"purpose":[60],"this":[62,202],"paper":[63,84],"analyze":[66],"features":[69,78,277],"an":[71,154],"video":[73,217],"extract":[75],"that":[79,164,233],"empathize.":[82],"This":[83],"combines":[85],"both":[86],"methods":[87],"power":[90],"spectrum":[91],"MFCC":[93],"image":[95,276],"RGB":[96],"analysis":[97,112],"find":[99],"audio":[101,195,214,236,256,279],"feature":[102,196,268],"vector.":[103],"In":[104],"spectral":[105],"analysis,":[106],"eigenvectors":[108],"obtained":[109,139,169],"process":[113],"range":[114],"from":[115],"blue":[116],"(low":[117],"range)":[118,122],"green":[120],"(medium":[121],"red":[124],"(high":[125],"range).":[126],"machine":[128,141,250],"learning":[129,251],"random":[130],"forest":[131],"classifier":[132],"used":[134,148],"classify":[136],"data":[138],"by":[140,189,244,271],"learning,":[142],"trained":[145],"model":[146,167],"monitor":[150],"development":[152],"advertisement":[155],"system":[157],"real":[159],"time.":[160],"result":[162,174],"optimal":[166],"with":[170],"training":[172],"accuracy":[173,180],"99.173%":[176],"test":[179],"86.171%,":[182],"be":[185,205],"deemed":[186],"as":[187,207],"correct":[188],"comparing":[190],"three":[192],"models":[193],"value":[197,269],"analysis.":[198],"contribution":[200],"study":[203],"summarized":[206],"follows:":[208],"(1)":[209],"low-frequency":[211],"high-amplitude":[213,227],"more":[219],"likely":[220],"resonate":[222],"than":[223],"high-frequency":[225],"audio;":[228],"(2)":[229],"found":[232],"frequency":[234],"amplitude":[237],"are":[238],"attributes":[240],"describing":[242],"waveforms":[243],"observing":[245],"characteristics":[247],"classifier;":[252],"(3)":[253],"new":[255],"extraction":[257],"method":[258,273],"proposed":[260],"induce":[262],"empathy.":[264,287],"That":[265],"is,":[266],"extracted":[270],"spectrogram":[275],"most":[282],"ability":[283],"arouse":[285]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
