{"id":"https://openalex.org/W7166543303","doi":"https://doi.org/10.48550/arxiv.2606.27627","title":"HybridCodec: Modeling Discrete and Continuous Representations for Efficient Speech Language Models","display_name":"HybridCodec: Modeling Discrete and Continuous Representations for Efficient Speech Language Models","publication_year":2026,"publication_date":"2026-06-26","ids":{"openalex":"https://openalex.org/W7166543303","doi":"https://doi.org/10.48550/arxiv.2606.27627"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.27627","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.27627","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.27627","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5063047435","display_name":"Artem Ploujnikov","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ploujnikov, Artem","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114414247","display_name":"Francesco Verdini","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Verdini, Francesco","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021724743","display_name":"Samir Sadok","orcid":"https://orcid.org/0009-0007-5956-4133"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sadok, Samir","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139585506","display_name":"Mirco Ravanelli","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ravanelli, Mirco","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":0.5821999907493591,"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":0.5821999907493591,"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/T11309","display_name":"Music and Audio Processing","score":0.14380000531673431,"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/T10860","display_name":"Speech and Audio Processing","score":0.13830000162124634,"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/autoregressive-model","display_name":"Autoregressive model","score":0.7267000079154968},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5480999946594238},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.5367000102996826},{"id":"https://openalex.org/keywords/codec","display_name":"Codec","score":0.487199991941452},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.48240000009536743},{"id":"https://openalex.org/keywords/speech-coding","display_name":"Speech coding","score":0.38269999623298645},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.37619999051094055},{"id":"https://openalex.org/keywords/voice-activity-detection","display_name":"Voice activity detection","score":0.36500000953674316}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7742999792098999},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.7267000079154968},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.597000002861023},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5480999946594238},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5367000102996826},{"id":"https://openalex.org/C161765866","wikidata":"https://www.wikidata.org/wiki/Q184748","display_name":"Codec","level":2,"score":0.487199991941452},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.48240000009536743},{"id":"https://openalex.org/C13895895","wikidata":"https://www.wikidata.org/wiki/Q3270773","display_name":"Speech coding","level":2,"score":0.38269999623298645},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.37619999051094055},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36890000104904175},{"id":"https://openalex.org/C204201278","wikidata":"https://www.wikidata.org/wiki/Q1332614","display_name":"Voice activity detection","level":3,"score":0.36500000953674316},{"id":"https://openalex.org/C61328038","wikidata":"https://www.wikidata.org/wiki/Q3358061","display_name":"Speech processing","level":2,"score":0.3610999882221222},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.335999995470047},{"id":"https://openalex.org/C55689738","wikidata":"https://www.wikidata.org/wiki/Q15963867","display_name":"Discrete time and continuous time","level":2,"score":0.3287999927997589},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.3109000027179718},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.30399999022483826},{"id":"https://openalex.org/C179603123","wikidata":"https://www.wikidata.org/wiki/Q1941921","display_name":"Modeling language","level":3,"score":0.29980000853538513},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.2904999852180481},{"id":"https://openalex.org/C177291462","wikidata":"https://www.wikidata.org/wiki/Q423038","display_name":"Active listening","level":2,"score":0.2831000089645386},{"id":"https://openalex.org/C2779679103","wikidata":"https://www.wikidata.org/wiki/Q5251805","display_name":"Degradation (telecommunications)","level":2,"score":0.2736999988555908},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.27059999108314514},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.257099986076355}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.27627","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.27627","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.27627","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.27627","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":"Preprint"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.5999590754508972,"id":"https://metadata.un.org/sdg/4"}],"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],"audio":[1,14],"representations":[2],"have":[3],"become":[4],"increasingly":[5],"popular":[6],"for":[7],"building":[8],"multimodal":[9],"text-audio":[10],"systems":[11],"and":[12,64,81],"integrating":[13],"capabilities":[15],"into":[16],"Large":[17],"Language":[18],"Models":[19],"(LLMs).":[20],"However,":[21],"numerous":[22],"studies":[23],"report":[24],"performance":[25],"degradation":[26],"on":[27],"various":[28],"downstream":[29],"tasks":[30],"due":[31],"to":[32,99],"information":[33],"loss":[34],"during":[35],"discretization.":[36],"To":[37],"address":[38],"this,":[39],"we":[40],"propose":[41],"a":[42,58,65],"novel":[43],"approach":[44,90],"combining":[45],"temporally":[46],"compressed":[47],"discrete":[48,75],"tokens":[49],"with":[50,78],"dimensionality-reduced":[51],"continuous":[52,82],"residuals.":[53],"Our":[54],"framework":[55],"consists":[56],"of":[57,95,107],"hybridized":[59],"discrete-continuous":[60],"focal":[61],"modulation":[62],"codec":[63],"hybrid":[66],"Transformer.":[67],"This":[68],"architecture":[69],"performs":[70],"autoregressive":[71,109],"inference":[72],"in":[73],"the":[74,93,105],"domain,":[76],"coupled":[77],"non-autoregressive":[79],"prediction":[80],"residual":[83],"upsampling.":[84],"Experimental":[85],"results":[86],"show":[87],"that":[88],"our":[89],"significantly":[91],"improves":[92],"retention":[94],"speaker":[96],"characteristics":[97],"compared":[98],"discrete-only":[100],"methods,":[101],"while":[102],"simultaneously":[103],"reducing":[104],"number":[106],"required":[108],"steps.":[110]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-30T00:00:00"}
