{"id":"https://openalex.org/W7163916875","doi":"https://doi.org/10.48550/arxiv.2606.06806","title":"Leveraging Soft Distributions of SSL-Derived Discrete Speech Tokens for Downstream Inference","display_name":"Leveraging Soft Distributions of SSL-Derived Discrete Speech Tokens for Downstream Inference","publication_year":2026,"publication_date":"2026-06-05","ids":{"openalex":"https://openalex.org/W7163916875","doi":"https://doi.org/10.48550/arxiv.2606.06806"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.06806","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.06806","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.2606.06806","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5113361539","display_name":"Kentaro Onda","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Onda, Kentaro","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003098968","display_name":"Satoru Fukayama","orcid":"https://orcid.org/0000-0001-6506-2796"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fukayama, Satoru","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138117823","display_name":"Daisuke Saito","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Saito, Daisuke","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138144382","display_name":"Nobuaki Minematsu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Minematsu, Nobuaki","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/T10201","display_name":"Speech Recognition and Synthesis","score":0.947700023651123,"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":0.947700023651123,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.010599999688565731,"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/T10028","display_name":"Topic Modeling","score":0.007400000002235174,"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/security-token","display_name":"Security token","score":0.7394999861717224},{"id":"https://openalex.org/keywords/discretization","display_name":"Discretization","score":0.7141000032424927},{"id":"https://openalex.org/keywords/downstream","display_name":"Downstream (manufacturing)","score":0.7009000182151794},{"id":"https://openalex.org/keywords/generalizability-theory","display_name":"Generalizability theory","score":0.5715000033378601},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5637000203132629},{"id":"https://openalex.org/keywords/voice-activity-detection","display_name":"Voice activity detection","score":0.46889999508857727},{"id":"https://openalex.org/keywords/compression","display_name":"Compression (physics)","score":0.3797000050544739},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.3546000123023987}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7893999814987183},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.7394999861717224},{"id":"https://openalex.org/C73000952","wikidata":"https://www.wikidata.org/wiki/Q17007827","display_name":"Discretization","level":2,"score":0.7141000032424927},{"id":"https://openalex.org/C2776207758","wikidata":"https://www.wikidata.org/wiki/Q5303302","display_name":"Downstream (manufacturing)","level":2,"score":0.7009000182151794},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.5715000033378601},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5697000026702881},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5637000203132629},{"id":"https://openalex.org/C204201278","wikidata":"https://www.wikidata.org/wiki/Q1332614","display_name":"Voice activity detection","level":3,"score":0.46889999508857727},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43299999833106995},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.3797000050544739},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.3546000123023987},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.34209999442100525},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.33219999074935913},{"id":"https://openalex.org/C61328038","wikidata":"https://www.wikidata.org/wiki/Q3358061","display_name":"Speech processing","level":2,"score":0.3319000005722046},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.2976999878883362},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.28850001096725464},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.2874999940395355},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.2847000062465668},{"id":"https://openalex.org/C13895895","wikidata":"https://www.wikidata.org/wiki/Q3270773","display_name":"Speech coding","level":2,"score":0.2833000123500824},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.28200000524520874},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.26989999413490295},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.26930001378059387},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2599000036716461}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.06806","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.06806","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.2606.06806","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.06806","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":[{"id":"https://metadata.un.org/sdg/4","score":0.4298349916934967,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Discrete":[0],"speech":[1,87],"tokens":[2,73],"obtained":[3],"from":[4],"self-supervised":[5],"learning":[6],"(SSL)":[7],"models":[8,106],"provide":[9],"efficient":[10],"data":[11],"compression":[12],"while":[13,67],"maintaining":[14],"strong":[15,93],"performance,":[16],"and":[17,86,90],"have":[18],"been":[19],"widely":[20],"used":[21],"as":[22],"intermediate":[23],"representations":[24,116],"in":[25],"various":[26],"tasks.":[27],"However,":[28],"discretization":[29,64],"inevitably":[30],"causes":[31],"information":[32],"loss,":[33],"leading":[34],"to":[35,48,95],"degraded":[36],"performance":[37],"compared":[38,124],"with":[39,122,125],"continuous":[40,108],"SSL":[41,109],"features.":[42,110],"In":[43],"this":[44],"work,":[45],"we":[46],"propose":[47],"apply":[49],"soft":[50],"token":[51],"assignment":[52,82],"only":[53],"during":[54,65],"downstream":[55],"inference.":[56,75],"This":[57],"approach":[58],"preserves":[59],"the":[60,69,72,114],"efficiency":[61],"of":[62,71,100,113],"hard":[63,81,127],"training":[66],"enhancing":[68],"expressiveness":[70],"at":[74],"The":[76],"proposed":[77],"method":[78],"outperforms":[79],"conventional":[80,126],"on":[83],"both":[84],"ASR":[85,99],"synthesis":[88],"tasks,":[89],"exhibits":[91],"particularly":[92],"generalizability":[94],"out-of-domain":[96],"data.":[97],"For":[98],"non-native":[101],"speech,":[102],"it":[103],"even":[104],"surpasses":[105],"using":[107],"Moreover,":[111],"analysis":[112],"resulting":[115],"shows":[117],"they":[118],"align":[119],"more":[120],"accurately":[121],"phonemes":[123],"assignment.":[128]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-09T00:00:00"}