{"id":"https://openalex.org/W4414199208","doi":"https://doi.org/10.1109/dac63849.2025.11132579","title":"SpecASR: Accelerating LLM-based Automatic Speech Recognition via Speculative Decoding","display_name":"SpecASR: Accelerating LLM-based Automatic Speech Recognition via Speculative Decoding","publication_year":2025,"publication_date":"2025-06-22","ids":{"openalex":"https://openalex.org/W4414199208","doi":"https://doi.org/10.1109/dac63849.2025.11132579"},"language":"en","primary_location":{"id":"doi:10.1109/dac63849.2025.11132579","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dac63849.2025.11132579","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 62nd ACM/IEEE Design Automation Conference (DAC)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101077258","display_name":"Lin Wei","orcid":"https://orcid.org/0000-0001-8334-8296"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Linye Wei","raw_affiliation_strings":["Institute for Artificial Intelligence, Peking University,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Institute for Artificial Intelligence, Peking University,Beijing,China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081222727","display_name":"Shuzhang Zhong","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]},{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuzhang Zhong","raw_affiliation_strings":["Institute for Artificial Intelligence, Peking University,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Institute for Artificial Intelligence, Peking University,Beijing,China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113389019","display_name":"Songqiang Xu","orcid":"https://orcid.org/0009-0001-8373-0732"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Songqiang Xu","raw_affiliation_strings":["Institute for Artificial Intelligence, Peking University,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Institute for Artificial Intelligence, Peking University,Beijing,China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002760019","display_name":"Runsheng Wang","orcid":"https://orcid.org/0000-0002-7514-0767"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Runsheng Wang","raw_affiliation_strings":["Peking University,School of Integrated Circuits,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Peking University,School of Integrated Circuits,Beijing,China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062886480","display_name":"Ru Huang","orcid":"https://orcid.org/0000-0002-8146-4821"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ru Huang","raw_affiliation_strings":["Peking University,School of Integrated Circuits,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Peking University,School of Integrated Circuits,Beijing,China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100457502","display_name":"Meng Li","orcid":"https://orcid.org/0000-0002-7212-2264"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]},{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meng Li","raw_affiliation_strings":["Institute for Artificial Intelligence, Peking University,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Institute for Artificial Intelligence, Peking University,Beijing,China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5101077258"],"corresponding_institution_ids":["https://openalex.org/I20231570","https://openalex.org/I4210100255"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13481121,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9919000267982483,"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":0.9919000267982483,"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/T10860","display_name":"Speech and Audio Processing","score":0.9546999931335449,"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/decoding-methods","display_name":"Decoding methods","score":0.8787000179290771},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.8004000186920166},{"id":"https://openalex.org/keywords/sequential-decoding","display_name":"Sequential decoding","score":0.5418000221252441},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5414999723434448},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.5056999921798706},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.46720001101493835},{"id":"https://openalex.org/keywords/low-latency","display_name":"Low latency (capital markets)","score":0.4629000127315521},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4302999973297119}],"concepts":[{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.8787000179290771},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.8004000186920166},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.794700026512146},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6739000082015991},{"id":"https://openalex.org/C193969084","wikidata":"https://www.wikidata.org/wiki/Q7452500","display_name":"Sequential decoding","level":4,"score":0.5418000221252441},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5414999723434448},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.5056999921798706},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.46720001101493835},{"id":"https://openalex.org/C46637626","wikidata":"https://www.wikidata.org/wiki/Q6693015","display_name":"Low latency (capital markets)","level":2,"score":0.4629000127315521},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4302999973297119},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.4244000017642975},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40779998898506165},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.3637999892234802},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.32420000433921814},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.2897999882698059},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.2867000102996826},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.2847999930381775},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2825999855995178},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.2606000006198883},{"id":"https://openalex.org/C13895895","wikidata":"https://www.wikidata.org/wiki/Q3270773","display_name":"Speech coding","level":2,"score":0.257099986076355},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.25619998574256897},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2556000053882599},{"id":"https://openalex.org/C40506919","wikidata":"https://www.wikidata.org/wiki/Q7452469","display_name":"Sequence learning","level":2,"score":0.2538999915122986}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/dac63849.2025.11132579","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dac63849.2025.11132579","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 62nd ACM/IEEE Design Automation Conference (DAC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W1494198834","https://openalex.org/W3097777922","https://openalex.org/W4391021666","https://openalex.org/W4392903956","https://openalex.org/W4404782770","https://openalex.org/W4408355893","https://openalex.org/W4410145879"],"related_works":[],"abstract_inverted_index":{"Large":[0],"language":[1],"model":[2,158],"(LLM)-based":[3],"automatic":[4],"speech":[5],"recognition":[6,19,210],"(ASR)":[7],"has":[8,40],"recently":[9],"attracted":[10],"a":[11,73,141,161],"lot":[12],"of":[13,30,53,175],"attention":[14],"due":[15],"to":[16,132,153,171],"its":[17],"high":[18,27,99],"accuracy":[20],"and":[21,57,104,177,192,202],"enhanced":[22],"multi-dialect":[23],"support.":[24],"However,":[25],"the":[26,33,50,54,64,128,134,148,155,173,198],"decoding":[28,39,45,76,93,114,201],"latency":[29,174],"LLMs":[31],"challenges":[32],"real-time":[34,65],"ASR":[35,55,66,92,106,157,179],"requirements.":[36],"Although":[37],"speculative":[38,75,203],"been":[41],"explored":[42],"for":[43,79],"better":[44],"efficiency,":[46],"they":[47],"usually":[48],"ignore":[49],"key":[51],"characteristics":[52],"task":[56],"achieve":[58],"limited":[59],"speedup.":[60],"To":[61],"further":[62,139],"reduce":[63,154],"latency,":[67],"in":[68,98,112,209],"this":[69],"paper,":[70],"we":[71,185],"propose":[72],"novel":[74],"framework":[77],"specialized":[78],"ASR,":[80],"dubbed":[81],"SpecASR.":[82],"SpecASR":[83,117,138,187],"is":[84,94,168],"developed":[85],"based":[86],"on":[87],"our":[88],"core":[89],"observation":[90],"that":[91,125,146],"audio-conditioned,":[95],"which":[96],"results":[97],"output":[100,110],"alignment":[101],"between":[102],"small":[103],"large":[105],"models,":[107],"even":[108],"given":[109],"mismatches":[111],"intermediate":[113],"steps.":[115],"Therefore,":[116],"features":[118],"an":[119],"adaptive":[120],"draft":[121,129,142,151,156,176],"sequence":[122,130,143,152],"generation":[123,166],"process":[124],"dynamically":[126],"modifies":[127],"length":[131],"maximize":[133],"token":[135,164],"acceptance":[136],"length.":[137],"proposes":[140],"recycling":[144],"strategy":[145],"reuses":[147],"previously":[149],"generated":[150],"latency.":[159],"Moreover,":[160],"two-pass":[162],"sparse":[163],"tree":[165],"algorithm":[167],"also":[169],"proposed":[170],"balance":[172],"target":[178],"models.":[180],"With":[181],"extensive":[182],"experimental":[183],"results,":[184],"demonstrate":[186],"achieves":[188],"$3.04":[189],"\\times-3.79":[190],"\\times$":[191,195],"$1.25":[193],"\\times-1.84":[194],"speedup":[196],"over":[197],"baseline":[199],"autoregressive":[200],"decoding,":[204],"respectively,":[205],"without":[206],"any":[207],"loss":[208],"accuracy.":[211]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-10T00:00:00"}
