{"id":"https://openalex.org/W7155158103","doi":"https://doi.org/10.48550/arxiv.2604.19532","title":"BEAT: Tokenizing and Generating Symbolic Music by Uniform Temporal Steps","display_name":"BEAT: Tokenizing and Generating Symbolic Music by Uniform Temporal Steps","publication_year":2026,"publication_date":"2026-04-21","ids":{"openalex":"https://openalex.org/W7155158103","doi":"https://doi.org/10.48550/arxiv.2604.19532"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.19532","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.19532","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.19532","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134360463","display_name":"Lekai Qian","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qian, Lekai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124177003","display_name":"Haoyu Gu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gu, Haoyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134310462","display_name":"Jingwei Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Jingwei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134361613","display_name":"Ziyu Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Ziyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"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":false,"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":false,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.6172999739646912,"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":0.6172999739646912,"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":0.21879999339580536,"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"}},{"id":"https://openalex.org/T10788","display_name":"Neuroscience and Music Perception","score":0.07859999686479568,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/musical","display_name":"Musical","score":0.6305000185966492},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.5175999999046326},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.4634000062942505},{"id":"https://openalex.org/keywords/lexical-analysis","display_name":"Lexical analysis","score":0.41850000619888306},{"id":"https://openalex.org/keywords/the-symbolic","display_name":"The Symbolic","score":0.4081999957561493},{"id":"https://openalex.org/keywords/musical-notation","display_name":"Musical notation","score":0.3546999990940094}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6919000148773193},{"id":"https://openalex.org/C558565934","wikidata":"https://www.wikidata.org/wiki/Q2743","display_name":"Musical","level":2,"score":0.6305000185966492},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5440999865531921},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.5175999999046326},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.4634000062942505},{"id":"https://openalex.org/C176982825","wikidata":"https://www.wikidata.org/wiki/Q835922","display_name":"Lexical analysis","level":2,"score":0.41850000619888306},{"id":"https://openalex.org/C2776095079","wikidata":"https://www.wikidata.org/wiki/Q489538","display_name":"The Symbolic","level":2,"score":0.4081999957561493},{"id":"https://openalex.org/C88639978","wikidata":"https://www.wikidata.org/wiki/Q233861","display_name":"Musical notation","level":3,"score":0.3546999990940094},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3492000102996826},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.32820001244544983},{"id":"https://openalex.org/C196017715","wikidata":"https://www.wikidata.org/wiki/Q862597","display_name":"Musical form","level":3,"score":0.322299987077713},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.32109999656677246},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2906999886035919},{"id":"https://openalex.org/C88626702","wikidata":"https://www.wikidata.org/wiki/Q1128903","display_name":"Continuation","level":2,"score":0.28949999809265137},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.27230000495910645},{"id":"https://openalex.org/C109568592","wikidata":"https://www.wikidata.org/wiki/Q207628","display_name":"Musical composition","level":3,"score":0.26930001378059387},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.25200000405311584}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.19532","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.19532","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.19532","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.19532","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Tokenizing":[0],"music":[1,22,37,148],"to":[2],"fit":[3],"the":[4,16,67,106,120,144,182],"general":[5],"framework":[6],"of":[7,40,69,138,178],"language":[8],"models":[9],"is":[10,55,94],"a":[11,97,102,115,135,139],"compelling":[12],"challenge,":[13],"especially":[14],"considering":[15],"diverse":[17],"symbolic":[18,36],"structures":[19],"in":[20,61,80],"which":[21,133],"can":[23],"be":[24],"represented":[25],"(e.g.,":[26,101],"sequences,":[27],"grids,":[28],"and":[29,57,126,150,165,174],"graphs).":[30],"To":[31],"date,":[32],"most":[33],"approaches":[34],"tokenize":[35],"as":[38,44,105,123],"sequences":[39],"musical":[41,70,99,163],"events,":[42],"such":[43],"onsets,":[45],"pitches,":[46],"time":[47,71,82,117,131],"shifts,":[48],"or":[49],"compound":[50],"note":[51],"events.":[52],"This":[53],"strategy":[54],"intuitive":[56],"has":[58],"proven":[59],"effective":[60,176],"Transformer-based":[62],"models,":[63],"but":[64],"it":[65,155],"treats":[66],"regularity":[68],"implicitly:":[72],"individual":[73],"tokens":[74,128],"may":[75],"span":[76],"different":[77],"durations,":[78],"resulting":[79],"non-uniform":[81],"progression.":[83],"In":[84],"this":[85],"paper,":[86],"we":[87,110],"instead":[88],"consider":[89],"whether":[90],"an":[91],"alternative":[92],"tokenization":[93,146],"possible,":[95],"where":[96],"uniform-length":[98],"step":[100,118],"beat)":[103],"serves":[104],"basic":[107],"unit.":[108],"Specifically,":[109],"encode":[111],"all":[112],"events":[113],"within":[114],"single":[116],"at":[119],"same":[121],"pitch":[122],"one":[124],"token,":[125],"group":[127],"explicitly":[129],"by":[130],"step,":[132],"resembles":[134],"sparse":[136],"encoding":[137],"piano-roll":[140],"representation.":[141],"We":[142],"evaluate":[143],"proposed":[145,183],"on":[147],"continuation":[149],"accompaniment":[151],"generation":[152],"tasks,":[153],"comparing":[154],"with":[156,181],"mainstream":[157],"event-based":[158],"methods.":[159],"Results":[160],"show":[161],"improved":[162],"quality":[164],"structural":[166],"coherence,":[167],"while":[168],"additional":[169],"analyses":[170],"confirm":[171],"higher":[172],"efficiency":[173],"more":[175],"capture":[177],"long-range":[179],"patterns":[180],"tokenization.":[184]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-23T00:00:00"}
