{"id":"https://openalex.org/W7052106923","doi":null,"title":"Possibilities of convolutions in AI-reconstructed music","display_name":"Possibilities of convolutions in AI-reconstructed music","publication_year":2024,"publication_date":"2024-11-08","ids":{"openalex":"https://openalex.org/W7052106923"},"language":"en","primary_location":{"id":"pmh:oai:osuva.uwasa.fi:10024/18461","doi":null,"is_oa":true,"landing_page_url":"https://osuva.uwasa.fi/handle/10024/18461","pdf_url":"https://osuva.uwasa.fi/bitstreams/7849832c-b6ca-49a4-8ee1-44d3a7c4e896/download","source":{"id":"https://openalex.org/S4306400974","display_name":"Osuva (University of Vaasa)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I79765343","host_organization_name":"University of Vaasa","host_organization_lineage":["https://openalex.org/I79765343"],"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":null,"raw_type":"fi=Diplomity\u00f6|en=Master's thesis (M.Sc. (Tech.))|sv=Diplomarbete|"},"volume":null,"type":"dissertation","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://osuva.uwasa.fi/bitstreams/7849832c-b6ca-49a4-8ee1-44d3a7c4e896/download","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Mets\u00e4l\u00e4, Mikael","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Mets\u00e4l\u00e4, Mikael","raw_affiliation_strings":["Automation and Computer Science"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Automation and Computer Science","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9570000171661377,"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":0.9570000171661377,"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":0.019999999552965164,"subfield":{"id":"https://openalex.org/subfields/1210","display_name":"Music"},"field":{"id":"https://openalex.org/fields/12","display_name":"Arts and Humanities"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.01730000041425228,"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/convolutional-autoencoder","display_name":"convolutional autoencoder","score":0.8830000162124634},{"id":"https://openalex.org/keywords/sound-reconstruction","display_name":"audio reconstruction","score":0.9399999976158142},{"id":"https://openalex.org/keywords/resource-constrained-devices","display_name":"resource-constrained devices","score":0.6700000166893005},{"id":"https://openalex.org/keywords/sound-synthesis","display_name":"sound synthesis","score":0.6700000166893005},{"id":"https://openalex.org/keywords/musical-analysis","display_name":"musical analysis","score":0.8240000009536743},{"id":"https://openalex.org/keywords/spectral-representation","display_name":"spectral representation","score":0.652999997138977},{"id":"https://openalex.org/keywords/low-frequency-components","display_name":"low-frequency components","score":0.5910000205039978}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.7567999958992004},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6869999766349792},{"id":"https://openalex.org/C157899210","wikidata":"https://www.wikidata.org/wiki/Q1395022","display_name":"Convolutional code","level":3,"score":0.6607999801635742},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5034999847412109},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49959999322891235},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4805000126361847},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4377000033855438},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.42660000920295715},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.41769999265670776},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4027000069618225},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.3698999881744385},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.3668000102043152},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3643999993801117},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3447999954223633},{"id":"https://openalex.org/C2779106878","wikidata":"https://www.wikidata.org/wiki/Q1257510","display_name":"Digital audio broadcasting","level":2,"score":0.31929999589920044},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.30630001425743103},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.3061000108718872},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.3061000108718872},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2870999872684479},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.2838999927043915},{"id":"https://openalex.org/C167085575","wikidata":"https://www.wikidata.org/wiki/Q6803654","display_name":"Mean squared prediction error","level":2,"score":0.27730000019073486},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.27469998598098755},{"id":"https://openalex.org/C57869625","wikidata":"https://www.wikidata.org/wiki/Q1783502","display_name":"Rate of convergence","level":3,"score":0.26109999418258667},{"id":"https://openalex.org/C64922751","wikidata":"https://www.wikidata.org/wiki/Q4650799","display_name":"Audio signal","level":3,"score":0.2605000138282776}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:osuva.uwasa.fi:10024/18461","doi":null,"is_oa":true,"landing_page_url":"https://osuva.uwasa.fi/handle/10024/18461","pdf_url":"https://osuva.uwasa.fi/bitstreams/7849832c-b6ca-49a4-8ee1-44d3a7c4e896/download","source":{"id":"https://openalex.org/S4306400974","display_name":"Osuva (University of Vaasa)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I79765343","host_organization_name":"University of Vaasa","host_organization_lineage":["https://openalex.org/I79765343"],"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":null,"raw_type":"fi=Diplomity\u00f6|en=Master's thesis (M.Sc. (Tech.))|sv=Diplomarbete|"},{"id":"pmh:oai:osuva.uwasa.fi:11111/11986","doi":null,"is_oa":true,"landing_page_url":"https://osuva.uwasa.fi/handle/11111/11986","pdf_url":null,"source":{"id":"https://openalex.org/S4306400974","display_name":"Osuva (University of Vaasa)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I79765343","host_organization_name":"University of Vaasa","host_organization_lineage":["https://openalex.org/I79765343"],"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":"https://osuva.uwasa.fi/handle/10024/18461","raw_type":"fi=Diplomity\u00f6|en=Master's thesis (M.Sc. (Tech.))|sv=Diplomarbete|"}],"best_oa_location":{"id":"pmh:oai:osuva.uwasa.fi:10024/18461","doi":null,"is_oa":true,"landing_page_url":"https://osuva.uwasa.fi/handle/10024/18461","pdf_url":"https://osuva.uwasa.fi/bitstreams/7849832c-b6ca-49a4-8ee1-44d3a7c4e896/download","source":{"id":"https://openalex.org/S4306400974","display_name":"Osuva (University of Vaasa)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I79765343","host_organization_name":"University of Vaasa","host_organization_lineage":["https://openalex.org/I79765343"],"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":null,"raw_type":"fi=Diplomity\u00f6|en=Master's thesis (M.Sc. (Tech.))|sv=Diplomarbete|"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7052106923.pdf","grobid_xml":"https://content.openalex.org/works/W7052106923.grobid-xml"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W1498436455","https://openalex.org/W1959608418","https://openalex.org/W2100495367","https://openalex.org/W2112796928","https://openalex.org/W2136922672","https://openalex.org/W2163922914","https://openalex.org/W2769810959","https://openalex.org/W2910068345","https://openalex.org/W2945020349","https://openalex.org/W2962942158","https://openalex.org/W2964121744","https://openalex.org/W3021164770","https://openalex.org/W3034429116","https://openalex.org/W3122425081","https://openalex.org/W3207924272","https://openalex.org/W4221152471","https://openalex.org/W4252713891","https://openalex.org/W4253161820","https://openalex.org/W4298289240","https://openalex.org/W4318351475","https://openalex.org/W4386826409","https://openalex.org/W4392077456","https://openalex.org/W4394030191","https://openalex.org/W4396685186"],"related_works":["https://openalex.org/W4402426944","https://openalex.org/W4364305679","https://openalex.org/W4408352691","https://openalex.org/W7125406784","https://openalex.org/W7130371324","https://openalex.org/W3192824065","https://openalex.org/W7168263196","https://openalex.org/W4406093011","https://openalex.org/W4403790838","https://openalex.org/W3109940347"],"abstract_inverted_index":{"This":[0,76,135],"thesis":[1],"investigates":[2],"the":[3,44,68,113,145,169,188,216,256,260,310],"application":[4],"of":[5,25,70,112,115,144,148,168,174,312,365],"convolutional":[6,32,80,120,189,222,241,281,344],"layers":[7,33,81,91],"within":[8,92,343],"an":[9],"autoencoder":[10,36,190],"to":[11,29,73,87,180,207,225,244,301],"reconstruct":[12],"one-dimensional":[13,129],"audio":[14,41,55,130,228,236,291,306,348,374],"data":[15,292],"in":[16,267,273,309,369],"systems":[17],"with":[18,251],"limited":[19,94],"computational":[20],"resources.":[21],"The":[22,184,240,296],"primary":[23,170],"objective":[24],"this":[26,99,360],"study":[27,77,297,361],"is":[28],"explore":[30],"whether":[31],"could":[34,283],"improve":[35],"performance":[37,114],"by":[38,197],"retaining":[39],"key":[40,158],"characteristics":[42],"during":[43],"reconstruction":[45],"process.":[46],"While":[47],"deep":[48],"generative":[49],"models":[50],"have":[51],"shown":[52],"promise":[53],"for":[54,138,288,316],"synthesis,":[56],"research":[57,336],"has":[58],"predominantly":[59],"focused":[60],"on":[61,128,230,293,339,357],"large-scale":[62],"implementations,":[63],"leaving":[64],"open":[65],"questions":[66],"about":[67],"adaptability":[69],"these":[71,277],"approaches":[72],"smaller":[74,231,358],"systems.":[75],"hypothesized":[78],"that":[79,187,280,354],"would":[82],"enable":[83],"improved":[84],"reconstructions":[85],"compared":[86],"fully":[88,117],"connected":[89,118],"(FC)":[90],"a":[93,101,109,139,154,285],"VRAM":[95],"environment.":[96],"To":[97,152],"test":[98],"hypothesis,":[100,261],"controlled":[102],"experimental":[103],"approach":[104,136,287],"was":[105,124],"employed,":[106],"which":[107],"involved":[108],"detailed":[110],"comparison":[111],"both":[116,274],"and":[119,141,177,203,250,304,328,331,346,372],"architectures.":[121],"Each":[122],"model":[123,150,182,258,314],"trained":[125],"from":[126],"scratch":[127],"sequences":[131],"until":[132],"reaching":[133],"convergence.":[134],"allowed":[137],"clear":[140],"precise":[142],"evaluation":[143],"relative":[146],"effectiveness":[147],"each":[149],"type.":[151],"ensure":[153],"comprehensive":[155],"assessment,":[156],"several":[157],"metrics":[159],"were":[160,271],"selected,":[161],"including":[162],"mean":[163,200],"squared":[164,201],"error":[165,202],"as":[166,195,265,323],"one":[167],"metrics,":[171],"alongside":[172],"observations":[173],"convergence":[175],"rate":[176],"memory":[178],"efficiency":[179],"evaluate":[181],"performance.":[183],"findings":[185],"indicate":[186],"achieved":[191],"superior":[192],"reconstruc-tion":[193,229],"quality,":[194],"evidenced":[196],"its":[198],"lower":[199],"faster":[204],"epoch-wise":[205],"progres-sion":[206],"accuracy,":[208],"despite":[209],"taking":[210],"slightly":[211],"longer":[212],"per":[213],"epoch":[214],"than":[215,255],"FC":[217,257],"model.":[218],"These":[219],"results":[220,278],"highlight":[221],"architectures'":[223],"potential":[224],"facilitate":[226],"high-quality":[227],"systems,":[232,359],"making":[233],"advanced":[234],"AI-driven":[235],"analysis":[237,303,371],"more":[238,248],"accessible.":[239],"model\u2019s":[242],"ability":[243],"represent":[245],"low-frequency":[246],"components":[247],"effectively":[249,356],"less":[252],"added":[253],"noise":[254],"supports":[259],"although":[262],"challeng-es,":[263],"such":[264,322],"limitations":[266],"replicating":[268],"high-frequency":[269],"components,":[270],"noted":[272],"models.":[275],"Overall,":[276],"suggest":[279],"autoencoders":[282],"offer":[284],"prom-ising":[286],"efficiently":[289],"reconstructing":[290],"constrained":[294],"hardware.":[295],"contributes":[298],"valuable":[299],"insights":[300],"music":[302,370],"AI":[305,367],"research,":[307],"particularly":[308],"context":[311],"scalable":[313],"design":[315],"low-resource":[317],"environments.":[318],"It":[319],"acknowledges":[320],"limitations,":[321],"subjective":[324],"sound":[325],"quality":[326],"assessment":[327],"hardware":[329],"constraints,":[330],"recommends":[332],"future":[333],"work.":[334],"Further":[335],"might":[337],"focus":[338],"enhancing":[340],"frequency":[341],"representation":[342],"networks":[345],"improving":[347],"separation":[349],"capabilities.":[350],"By":[351],"advancing":[352],"methods":[353],"operate":[355],"encourages":[362],"further":[363],"exploration":[364],"accessible":[366],"applications":[368],"digital":[373],"processing.":[375]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2025-10-10T00:00:00"}