{"id":"https://openalex.org/W7165139262","doi":"https://doi.org/10.48550/arxiv.2606.18323","title":"Reliable Neural-Codec Text-to-Speech by ASR Self-Verification and Distillation: Near-Zero Catastrophic Failures Across Models and Codecs","display_name":"Reliable Neural-Codec Text-to-Speech by ASR Self-Verification and Distillation: Near-Zero Catastrophic Failures Across Models and Codecs","publication_year":2026,"publication_date":"2026-06-16","ids":{"openalex":"https://openalex.org/W7165139262","doi":"https://doi.org/10.48550/arxiv.2606.18323"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.18323","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.18323","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":"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.2606.18323","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5138402369","display_name":"Ali Asaria","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Asaria, Ali","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138467146","display_name":"Tony Salomone","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Salomone, Tony","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138831031","display_name":"Deep Gandhi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gandhi, Deep","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/T10028","display_name":"Topic Modeling","score":0.2750000059604645,"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/T10028","display_name":"Topic Modeling","score":0.2750000059604645,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.163100004196167,"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":0.1160999983549118,"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/robustness","display_name":"Robustness (evolution)","score":0.5838000178337097},{"id":"https://openalex.org/keywords/catastrophic-failure","display_name":"Catastrophic failure","score":0.43950000405311584},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.3878999948501587},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.38600000739097595},{"id":"https://openalex.org/keywords/resampling","display_name":"Resampling","score":0.3375999927520752},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.3167000114917755}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7075999975204468},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5838000178337097},{"id":"https://openalex.org/C112987892","wikidata":"https://www.wikidata.org/wiki/Q5051574","display_name":"Catastrophic failure","level":2,"score":0.43950000405311584},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.3878999948501587},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.38600000739097595},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3582000136375427},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35510000586509705},{"id":"https://openalex.org/C150921843","wikidata":"https://www.wikidata.org/wiki/Q1170431","display_name":"Resampling","level":2,"score":0.3375999927520752},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.31679999828338623},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.3167000114917755},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.3127000033855438},{"id":"https://openalex.org/C161765866","wikidata":"https://www.wikidata.org/wiki/Q184748","display_name":"Codec","level":2,"score":0.29420000314712524},{"id":"https://openalex.org/C2911011789","wikidata":"https://www.wikidata.org/wiki/Q130741","display_name":"Hallucinating","level":2,"score":0.289900004863739},{"id":"https://openalex.org/C163164238","wikidata":"https://www.wikidata.org/wiki/Q2737027","display_name":"Failure rate","level":2,"score":0.2824000120162964},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.259799987077713}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.18323","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.18323","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":"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.2606.18323","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.18323","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":"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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Open":[0],"autoregressive":[1],"neural-codec":[2],"text-to-speech":[3],"(TTS)":[4],"models":[5],"sound":[6],"excellent":[7],"on":[8,16,68,76,110,147,164],"typical":[9],"inputs":[10,149],"yet":[11],"suffer":[12],"stochastic":[13],"catastrophic":[14],"failures:":[15],"a":[17,44,69,77,179,226],"meaningful":[18],"fraction":[19],"of":[20,86,112,135,143],"utterances":[21],"they":[22],"emit":[23],"silence,":[24],"terminate":[25],"early,":[26],"or":[27,31],"collapse":[28],"into":[29,129],"repetitive":[30],"hallucinated":[32],"content.":[33],"We":[34,115,208],"show":[35],"this":[36],"failure":[37,145],"mode":[38],"is":[39,82,160,168,198],"cheap":[40],"to":[41,60],"remove.":[42],"Under":[43],"single":[45],"format-robust":[46],"metric":[47],"(a":[48,216],"catastrophic-failure":[49],"rate":[50],"via":[51],"an":[52,84,194],"ASR":[53,56],"round-trip),":[54],"best-of-N":[55],"self-verification":[57],"drives":[58],"failures":[59,64],"near-zero:":[61],"no":[62,151,169,172,231],"observed":[63],"remain":[65],"by":[66,74,108,124],"N=2":[67,109],"standard":[70],"corpus":[71],"(LibriSpeech)":[72],"and":[73,97,171,193,225],"N=4":[75],"hard":[78,148],"prompt":[79],"set.":[80],"This":[81],"not":[83,188,201,222],"artifact":[85],"one":[87,212],"model:":[88],"the":[89,105,113,118,126,130,136,144,211],"reduction":[90],"replicates":[91],"across":[92],"four":[93],"open":[94],"codec-TTS":[95],"systems":[96],"three":[98,111],"neural":[99],"codecs":[100],"(XCodec2,":[101],"SNAC,":[102],"Mimi),":[103],"reaching":[104],"near-zero":[106],"floor":[107],"four.":[114],"then":[116],"make":[117],"fix":[119],"free":[120],"at":[121,150,204],"inference":[122],"time":[123],"distilling":[125],"self-verified":[127],"behaviour":[128],"model,":[131],"which":[132],"recovers":[133],"much":[134],"robustness":[137],"in":[138],"single-shot":[139],"decoding,":[140],"closing":[141],"~52-58%":[142],"mass":[146],"test-time":[152],"cost.":[153],"The":[154],"distillation":[155],"gain":[156],"concentrates":[157],"where":[158,219],"it":[159],"needed":[161],"(hard":[162],"inputs);":[163],"already-reliable":[165],"prose":[166],"there":[167],"headroom":[170],"detectable":[173],"change.":[174],"A":[175],"controlled":[176],"comparison":[177],"adds":[178],"clean":[180],"negative:":[181],"offline":[182],"direct":[183],"preference":[184],"optimization":[185],"(DPO/IPO)":[186],"does":[187],"beat":[189],"plain":[190],"supervised":[191],"distillation,":[192],"online":[195],"iterative":[196],"variant":[197],"promising":[199],"but":[200],"statistically":[202],"separable":[203],"our":[205],"evaluation":[206],"size.":[207],"report":[209],"honestly":[210],"model":[213],"that":[214,230],"resists":[215],"larger":[217],"Llasa":[218],"scale":[220],"did":[221],"obviously":[223],"help)":[224],"rare-word":[227],"capability":[228],"ceiling":[229],"self-distillation":[232],"method":[233],"overcomes":[234]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-19T00:00:00"}
