{"id":"https://openalex.org/W2403076886","doi":"https://doi.org/10.1109/icassp.2016.7471734","title":"A deep bidirectional long short-term memory based multi-scale approach for music dynamic emotion prediction","display_name":"A deep bidirectional long short-term memory based multi-scale approach for music dynamic emotion prediction","publication_year":2016,"publication_date":"2016-03-01","ids":{"openalex":"https://openalex.org/W2403076886","doi":"https://doi.org/10.1109/icassp.2016.7471734","mag":"2403076886"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2016.7471734","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2016.7471734","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5101733708","display_name":"Xinxing Li","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xinxing Li","raw_affiliation_strings":["Department of Computer Science and Technology Tsinghua University, Tsinghua National Laboratory for Information Science and Technology (TNList), Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology Tsinghua University, Tsinghua National Laboratory for Information Science and Technology (TNList), Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060610398","display_name":"Haishu Xianyu","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haishu Xianyu","raw_affiliation_strings":["Department of Computer Science and Technology Tsinghua University, Tsinghua National Laboratory for Information Science and Technology (TNList), Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology Tsinghua University, Tsinghua National Laboratory for Information Science and Technology (TNList), Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080684640","display_name":"Jiashen Tian","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiashen Tian","raw_affiliation_strings":["Department of Computer Science and Technology Tsinghua University, Tsinghua National Laboratory for Information Science and Technology (TNList), Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology Tsinghua University, Tsinghua National Laboratory for Information Science and Technology (TNList), Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030501342","display_name":"Wenxiao Chen","orcid":"https://orcid.org/0000-0001-8852-675X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenxiao Chen","raw_affiliation_strings":["Department of Computer Science and Technology Tsinghua University, Tsinghua National Laboratory for Information Science and Technology (TNList), Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology Tsinghua University, Tsinghua National Laboratory for Information Science and Technology (TNList), Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054216481","display_name":"Fanhang Meng","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fanhang Meng","raw_affiliation_strings":["Department of Computer Science and Technology Tsinghua University, Tsinghua National Laboratory for Information Science and Technology (TNList), Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology Tsinghua University, Tsinghua National Laboratory for Information Science and Technology (TNList), Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111983309","display_name":"Mingxing Xu","orcid":"https://orcid.org/0009-0000-3878-315X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingxing Xu","raw_affiliation_strings":["Department of Computer Science and Technology Tsinghua University, Tsinghua National Laboratory for Information Science and Technology (TNList), Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology Tsinghua University, Tsinghua National Laboratory for Information Science and Technology (TNList), Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053661520","display_name":"Lianhong Cai","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lianhong Cai","raw_affiliation_strings":["Department of Computer Science and Technology Tsinghua University, Tsinghua National Laboratory for Information Science and Technology (TNList), Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology Tsinghua University, Tsinghua National Laboratory for Information Science and Technology (TNList), Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5101733708"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":2.8058,"has_fulltext":false,"cited_by_count":58,"citation_normalized_percentile":{"value":0.9134621,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"544","last_page":"548"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9994000196456909,"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":0.9994000196456909,"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/T12676","display_name":"Machine Learning and ELM","score":0.9728999733924866,"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/T10320","display_name":"Neural Networks and Applications","score":0.9682000279426575,"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/long-short-term-memory","display_name":"Long short term memory","score":0.7395973205566406},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7327669858932495},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.6634691953659058},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5231695771217346},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4274354577064514},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3860102891921997},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2224682867527008},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.17897674441337585}],"concepts":[{"id":"https://openalex.org/C133488467","wikidata":"https://www.wikidata.org/wiki/Q6673524","display_name":"Long short term memory","level":4,"score":0.7395973205566406},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7327669858932495},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.6634691953659058},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5231695771217346},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4274354577064514},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3860102891921997},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2224682867527008},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.17897674441337585},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2016.7471734","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2016.7471734","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.4099999964237213,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W189934255","https://openalex.org/W1509691205","https://openalex.org/W1527033572","https://openalex.org/W1964357740","https://openalex.org/W2000497699","https://openalex.org/W2005708641","https://openalex.org/W2011853905","https://openalex.org/W2019010736","https://openalex.org/W2064675550","https://openalex.org/W2111072639","https://openalex.org/W2131774270","https://openalex.org/W2136848157","https://openalex.org/W2143612262","https://openalex.org/W2144499799","https://openalex.org/W2149628368","https://openalex.org/W2162092944","https://openalex.org/W2171848217","https://openalex.org/W2295276533","https://openalex.org/W2295959954","https://openalex.org/W2397756400","https://openalex.org/W2401248876","https://openalex.org/W2403697441","https://openalex.org/W2916566921","https://openalex.org/W6697249898"],"related_works":["https://openalex.org/W42295635","https://openalex.org/W1973996291","https://openalex.org/W2330575325","https://openalex.org/W4388747848","https://openalex.org/W2163803519","https://openalex.org/W2497592525","https://openalex.org/W3096145648","https://openalex.org/W3197510923","https://openalex.org/W2370579019","https://openalex.org/W4313265328"],"abstract_inverted_index":{"Music":[0,87],"Dynamic":[1],"Emotion":[2,85],"Prediction":[3],"is":[4],"a":[5,53],"challenging":[6],"and":[7,38,62],"significant":[8],"task.":[9],"In":[10],"this":[11],"paper,":[12],"We":[13,76],"adopt":[14],"the":[15,23,29,34,39,71,78,82,101],"dimensional":[16],"valence-arousal":[17],"(V-A)":[18],"emotion":[19,25],"model":[20],"to":[21,69],"represent":[22],"dynamic":[24],"in":[26,47,74,86,89],"music.":[27,75],"Considering":[28],"high":[30],"context":[31],"correlation":[32],"among":[33],"music":[35],"feature":[36],"sequence":[37,49],"advantage":[40],"of":[41,84,103],"Bidirectional":[42],"Long":[43],"Short-Term":[44],"Memory":[45],"(BLSTM)":[46],"capturing":[48],"information,":[50],"we":[51],"propose":[52],"multi-scale":[54,60,107],"approach,":[55],"Deep":[56],"BLSTM":[57],"(DBLSTM)":[58],"based":[59],"regression":[61],"fusion":[63],"with":[64,93],"Extreme":[65],"Learning":[66],"Machine":[67],"(ELM),":[68],"predict":[70],"V-A":[72],"values":[73],"achieved":[77],"best":[79],"performance":[80],"on":[81],"database":[83],"task":[88],"MediaEval":[90],"2015":[91],"compared":[92],"other":[94],"submitted":[95],"results.":[96],"The":[97],"experimental":[98],"results":[99],"demonstrated":[100],"effectiveness":[102],"our":[104],"novel":[105],"proposed":[106],"DBLSTM-ELM":[108],"model.":[109]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":24},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":4}],"updated_date":"2026-03-29T08:15:47.926485","created_date":"2025-10-10T00:00:00"}