{"id":"https://openalex.org/W7154449873","doi":"https://doi.org/10.48550/arxiv.2604.12383","title":"On the Distillation Loss Functions of Speech VAE for Unified Reconstruction, Understanding, and Generation","display_name":"On the Distillation Loss Functions of Speech VAE for Unified Reconstruction, Understanding, and Generation","publication_year":2026,"publication_date":"2026-04-14","ids":{"openalex":"https://openalex.org/W7154449873","doi":"https://doi.org/10.48550/arxiv.2604.12383"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.12383","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.12383","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.12383","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133710573","display_name":"Changhao Cheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cheng, Changhao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133647891","display_name":"Wei Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Wei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133695173","display_name":"Wangyou Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Wangyou","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060687079","display_name":"Dongya Jia","orcid":"https://orcid.org/0000-0002-6307-8580"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jia, Dongya","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133684203","display_name":"Jian Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Jian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133643581","display_name":"Zhuo Chen","orcid":"https://orcid.org/0009-0003-8329-7398"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Zhuo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133666579","display_name":"Yanmin Qian","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qian, Yanmin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.8091999888420105,"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"}},"topics":[{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.8091999888420105,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.061400000005960464,"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/T10860","display_name":"Speech and Audio Processing","score":0.031300000846385956,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.7060999870300293},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.6258000135421753},{"id":"https://openalex.org/keywords/spectrogram","display_name":"Spectrogram","score":0.5612999796867371},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.3562000095844269},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.3003999888896942}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7128999829292297},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.7060999870300293},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.6258000135421753},{"id":"https://openalex.org/C45273575","wikidata":"https://www.wikidata.org/wiki/Q578970","display_name":"Spectrogram","level":2,"score":0.5612999796867371},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5439000129699707},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39070001244544983},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.3562000095844269},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3231000006198883},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3003999888896942},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2955999970436096},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.260699987411499},{"id":"https://openalex.org/C61328038","wikidata":"https://www.wikidata.org/wiki/Q3358061","display_name":"Speech processing","level":2,"score":0.2517000138759613}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.12383","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.12383","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.12383","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.12383","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Continuous":[0],"speech":[1,23],"representations":[2,39],"based":[3,20,61],"on":[4,62,86],"Variational":[5],"Autoencoders":[6],"(VAEs)":[7],"have":[8],"emerged":[9],"as":[10],"a":[11,125],"promising":[12],"alternative":[13],"to":[14,31],"traditional":[15],"spectrogram":[16],"or":[17],"discrete":[18],"token":[19],"features":[21],"for":[22,48,124],"generation":[24,50],"and":[25,82,94],"reconstruction.":[26],"Recent":[27],"research":[28],"has":[29],"tried":[30],"enrich":[32],"the":[33,57,87,102,109,118],"structural":[34],"information":[35],"in":[36,101],"VAE":[37],"latent":[38],"by":[40],"aligning":[41],"with":[42,113],"self-supervised":[43],"learning":[44],"(SSL)":[45],"features,":[46],"aiming":[47],"better":[49],"performance.":[51],"However,":[52],"it":[53],"remains":[54],"unclear":[55],"whether":[56],"widely-used":[58],"alignment":[59,80,111],"approach":[60,112],"time-axis":[63],"distillation":[64,103],"is":[65],"optimal":[66],"when":[67],"considering":[68],"more":[69],"tasks.":[70],"To":[71],"address":[72],"this":[73,75],"problem,":[74],"paper":[76],"systematically":[77],"explores":[78],"different":[79],"approaches":[81],"analyzes":[83],"their":[84],"impact":[85],"performances":[88],"over":[89],"three":[90],"axes:":[91],"reconstruction,":[92],"understanding,":[93],"generation.":[95],"We":[96],"investigate":[97],"various":[98],"design":[99],"choices":[100],"loss.":[104],"Extensive":[105],"experiments":[106],"show":[107],"that":[108],"joint-marginal":[110],"adaptive":[114],"weighting":[115],"can":[116],"achieve":[117],"best":[119],"overall":[120],"performance":[121],"while":[122],"allowing":[123],"controllable":[126],"balance.":[127]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-04-16T00:00:00"}