{"id":"https://openalex.org/W7156852941","doi":"https://doi.org/10.48550/arxiv.2604.24416","title":"Scaling Properties of Continuous Diffusion Spoken Language Models","display_name":"Scaling Properties of Continuous Diffusion Spoken Language Models","publication_year":2026,"publication_date":"2026-04-27","ids":{"openalex":"https://openalex.org/W7156852941","doi":"https://doi.org/10.48550/arxiv.2604.24416"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.24416","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.24416","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2604.24416","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5020604198","display_name":"Jason Ramapuram","orcid":"https://orcid.org/0000-0001-9717-1188"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ramapuram, Jason","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044545212","display_name":"Eeshan Gunesh Dhekane","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dhekane, Eeshan Gunesh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126888004","display_name":"Amitis Shidani","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shidani, Amitis","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050567760","display_name":"Dan Busbridge","orcid":"https://orcid.org/0000-0002-2178-6917"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Busbridge, Dan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114106696","display_name":"Bogdan Mazoure","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mazoure, Bogdan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031982816","display_name":"Zijin Gu","orcid":"https://orcid.org/0000-0002-0385-2677"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gu, Zijin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110124828","display_name":"Russ Webb","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Webb, Russ","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134796502","display_name":"Tatiana Likhomanenko","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Likhomanenko, Tatiana","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5112445699","display_name":"Navdeep Jaitly","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jaitly, Navdeep","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":0.697700023651123,"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":0.697700023651123,"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":0.05079999938607216,"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/T11448","display_name":"Face recognition and analysis","score":0.039500001817941666,"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/mirroring","display_name":"Mirroring","score":0.8223999738693237},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.6452999711036682},{"id":"https://openalex.org/keywords/scaling","display_name":"Scaling","score":0.6251999735832214},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.6043999791145325},{"id":"https://openalex.org/keywords/discretization","display_name":"Discretization","score":0.5690000057220459},{"id":"https://openalex.org/keywords/coherence","display_name":"Coherence (philosophical gambling strategy)","score":0.553600013256073},{"id":"https://openalex.org/keywords/diffusion","display_name":"Diffusion","score":0.4977000057697296}],"concepts":[{"id":"https://openalex.org/C189645446","wikidata":"https://www.wikidata.org/wiki/Q350865","display_name":"Mirroring","level":2,"score":0.8223999738693237},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7037000060081482},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.6452999711036682},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.6251999735832214},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.6043999791145325},{"id":"https://openalex.org/C73000952","wikidata":"https://www.wikidata.org/wiki/Q17007827","display_name":"Discretization","level":2,"score":0.5690000057220459},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.553600013256073},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.4977000057697296},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.47200000286102295},{"id":"https://openalex.org/C2776230583","wikidata":"https://www.wikidata.org/wiki/Q1322198","display_name":"Spoken language","level":2,"score":0.44449999928474426},{"id":"https://openalex.org/C75778745","wikidata":"https://www.wikidata.org/wiki/Q342626","display_name":"Lag","level":2,"score":0.43689998984336853},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4343000054359436},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4253999888896942},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4171999990940094},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33500000834465027},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.32989999651908875},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.3190000057220459},{"id":"https://openalex.org/C155092808","wikidata":"https://www.wikidata.org/wiki/Q182557","display_name":"Computational linguistics","level":2,"score":0.31220000982284546},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.30959999561309814},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3037000000476837},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.26010000705718994}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.24416","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.24416","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2604.24416","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.24416","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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","display_name":"Quality Education","score":0.6366104483604431}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Speech-only":[0],"spoken":[1],"language":[2],"models":[3,10],"(SLMs)":[4],"lag":[5],"behind":[6],"text":[7,27],"and":[8,22,75,77,97],"text-speech":[9],"in":[11],"performance,":[12],"with":[13,111],"recent":[14],"discrete":[15],"autoregressive":[16],"(AR)":[17],"SLMs":[18,50,107],"indicating":[19],"significant":[20,134],"computational":[21],"data":[23,96,119],"demands":[24],"to":[25,93,108],"match":[26],"models.":[28],"Since":[29],"discretizing":[30],"continuous":[31,40],"speech":[32],"for":[33,72,87,102],"AR":[34,67],"creates":[35],"bottlenecks,":[36],"we":[37,53],"explore":[38],"whether":[39],"diffusion":[41],"(CD)":[42],"SLM":[43],"is":[44],"more":[45],"viable.":[46],"To":[47],"quantify":[48],"the":[49,55,88],"linguistic":[51],"quality,":[52],"introduce":[54],"phoneme":[56],"Jensen-Shannon":[57],"divergence":[58],"(pJSD)":[59],"metric.":[60],"Our":[61],"analysis":[62],"reveals":[63],"CD":[64,106],"SLMs,":[65],"mirroring":[66],"behavior,":[68],"exhibit":[69],"scaling":[70],"laws":[71],"validation":[73],"loss":[74,90],"pJSD,":[76],"show":[78],"optimal":[79],"token-to-parameter":[80],"ratios":[81],"decreasing":[82],"as":[83],"compute":[84],"scales.":[85],"However,":[86],"latter,":[89],"becomes":[91],"insensitive":[92],"choice":[94],"of":[95,113,115,117,122],"model":[98],"sizes,":[99],"showing":[100],"potential":[101],"fast":[103],"inference.":[104],"Scaling":[105],"16B":[109],"parameters":[110],"tens":[112],"millions":[114],"hours":[116],"conversational":[118],"enables":[120],"generation":[121],"emotive,":[123],"prosodic,":[124],"multi-speaker,":[125],"multilingual":[126],"speech,":[127],"though":[128],"achieving":[129],"long-form":[130],"coherence":[131],"remains":[132],"a":[133],"challenge.":[135]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-04-29T00:00:00"}