{"id":"https://openalex.org/W3091361158","doi":"https://doi.org/10.1109/iscas45731.2020.9181255","title":"Accurate Onset Detection Algorithm using Feature-Layer-Based Deep Learning Architecture","display_name":"Accurate Onset Detection Algorithm using Feature-Layer-Based Deep Learning Architecture","publication_year":2020,"publication_date":"2020-09-29","ids":{"openalex":"https://openalex.org/W3091361158","doi":"https://doi.org/10.1109/iscas45731.2020.9181255","mag":"3091361158"},"language":"en","primary_location":{"id":"doi:10.1109/iscas45731.2020.9181255","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas45731.2020.9181255","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Symposium on Circuits and Systems (ISCAS)","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/A5004221671","display_name":"Ping\u2010Hung Chen","orcid":"https://orcid.org/0000-0002-7156-0510"},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Ping-Hung Chen","raw_affiliation_strings":["Communication Engineering, National Taiwan University, Taipei, Taiwan"],"affiliations":[{"raw_affiliation_string":"Communication Engineering, National Taiwan University, Taipei, Taiwan","institution_ids":["https://openalex.org/I16733864"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022371410","display_name":"Jian\u2013Jiun Ding","orcid":"https://orcid.org/0000-0003-4510-2273"},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Jian-Jiun Ding","raw_affiliation_strings":["Communication Engineering, National Taiwan University, Taipei, Taiwan"],"affiliations":[{"raw_affiliation_string":"Communication Engineering, National Taiwan University, Taipei, Taiwan","institution_ids":["https://openalex.org/I16733864"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101926481","display_name":"Jinyu Huang","orcid":"https://orcid.org/0000-0002-4348-9796"},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Jin-Yu Huang","raw_affiliation_strings":["Communication Engineering, National Taiwan University, Taipei, Taiwan"],"affiliations":[{"raw_affiliation_string":"Communication Engineering, National Taiwan University, Taipei, Taiwan","institution_ids":["https://openalex.org/I16733864"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087493115","display_name":"Tzu-Yun Tseng","orcid":null},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Tzu-Yun Tseng","raw_affiliation_strings":["Communication Engineering, National Taiwan University, Taipei, Taiwan"],"affiliations":[{"raw_affiliation_string":"Communication Engineering, National Taiwan University, Taipei, Taiwan","institution_ids":["https://openalex.org/I16733864"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5004221671"],"corresponding_institution_ids":["https://openalex.org/I16733864"],"apc_list":null,"apc_paid":null,"fwci":0.3031,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.54608295,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9994000196456909,"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/T11349","display_name":"Music Technology and Sound Studies","score":0.9944000244140625,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.8241292238235474},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7096886038780212},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6676443219184875},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.5867605805397034},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5844476819038391},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.5820651650428772},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5377625823020935},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5319846868515015},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5166769027709961},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.4485074281692505},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.43547526001930237}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8241292238235474},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7096886038780212},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6676443219184875},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.5867605805397034},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5844476819038391},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.5820651650428772},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5377625823020935},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5319846868515015},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5166769027709961},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.4485074281692505},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.43547526001930237},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"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/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iscas45731.2020.9181255","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas45731.2020.9181255","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Symposium on Circuits and Systems (ISCAS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1526336542","https://openalex.org/W1966280390","https://openalex.org/W1985054298","https://openalex.org/W2083652170","https://openalex.org/W2091425152","https://openalex.org/W2115026158","https://openalex.org/W2119596759","https://openalex.org/W2139238328","https://openalex.org/W2140304104","https://openalex.org/W2194775991","https://openalex.org/W2578393854","https://openalex.org/W2794577896","https://openalex.org/W2808040094","https://openalex.org/W2911116331","https://openalex.org/W6677156367","https://openalex.org/W6678001420","https://openalex.org/W6751928219","https://openalex.org/W6758527138"],"related_works":["https://openalex.org/W2366107444","https://openalex.org/W4388145910","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3167935049","https://openalex.org/W3103566983","https://openalex.org/W3029198973"],"abstract_inverted_index":{"Onsets":[0],"are":[1],"criterion":[2],"points":[3],"to":[4,47],"separate":[5],"an":[6,34],"audio":[7],"signal":[8,61],"into":[9],"several":[10],"notes.":[11],"In":[12],"this":[13],"paper,":[14],"we":[15,43,66],"combine":[16],"the":[17,45,59,63,78,84],"advantages":[18],"of":[19],"conventional":[20],"rule-based":[21,41,93],"onset":[22,36,97],"detection":[23,37,98],"methods":[24,31],"and":[25,32,74,94],"convolutional":[26],"neural":[27],"network":[28],"(CNN)":[29],"based":[30],"propose":[33],"advanced":[35],"algorithm.":[38],"Different":[39,52],"from":[40,53],"methods,":[42,56],"apply":[44,58],"CNN":[46,79],"avoid":[48],"tuning":[49],"thresholds":[50],"empirically.":[51],"existing":[54,95],"CNN-based":[55,96],"which":[57],"original":[60],"as":[62,77],"input":[64],"directly,":[65],"construct":[67],"a":[68],"data":[69],"with":[70],"204":[71],"feature":[72],"layers":[73],"use":[75],"it":[76],"input.":[80],"Simulations":[81],"show":[82],"that":[83],"proposed":[85],"algorithm":[86],"has":[87],"much":[88],"better":[89],"performance":[90],"than":[91],"both":[92],"methods.":[99]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}