{"id":"https://openalex.org/W7163191931","doi":"https://doi.org/10.48550/arxiv.2606.01031","title":"Temporally-Aligned Evaluation for Audio-Driven Talking Head Generation","display_name":"Temporally-Aligned Evaluation for Audio-Driven Talking Head Generation","publication_year":2026,"publication_date":"2026-05-31","ids":{"openalex":"https://openalex.org/W7163191931","doi":"https://doi.org/10.48550/arxiv.2606.01031"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.01031","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.01031","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.2606.01031","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137692014","display_name":"Zhicheng Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Zhicheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137656879","display_name":"Lei P. Wang","orcid":"https://orcid.org/0000-0001-5614-6605"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Lei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137634706","display_name":"Yu Zhang","orcid":"https://orcid.org/0009-0009-3960-5852"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137679130","display_name":"Yongsheng Gao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gao, Yongsheng","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/T11448","display_name":"Face recognition and analysis","score":0.41780000925064087,"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"}},"topics":[{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.41780000925064087,"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"}},{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.10939999669790268,"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"}},{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.09849999845027924,"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/robustness","display_name":"Robustness (evolution)","score":0.7372000217437744},{"id":"https://openalex.org/keywords/dynamic-time-warping","display_name":"Dynamic time warping","score":0.7272999882698059},{"id":"https://openalex.org/keywords/image-warping","display_name":"Image warping","score":0.5200999975204468},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4943999946117401},{"id":"https://openalex.org/keywords/synchronization","display_name":"Synchronization (alternating current)","score":0.4878999888896942},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.460999995470047},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.44040000438690186}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7590000033378601},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7372000217437744},{"id":"https://openalex.org/C88516994","wikidata":"https://www.wikidata.org/wiki/Q1268863","display_name":"Dynamic time warping","level":2,"score":0.7272999882698059},{"id":"https://openalex.org/C157202957","wikidata":"https://www.wikidata.org/wiki/Q1659609","display_name":"Image warping","level":2,"score":0.5200999975204468},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5099999904632568},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4943999946117401},{"id":"https://openalex.org/C2778562939","wikidata":"https://www.wikidata.org/wiki/Q1298791","display_name":"Synchronization (alternating current)","level":3,"score":0.4878999888896942},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.460999995470047},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4438999891281128},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.44040000438690186},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.38100001215934753},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.34200000762939453},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.3093999922275543},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.28439998626708984},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.2815000116825104},{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.2734000086784363},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.26179999113082886}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.01031","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.01031","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.2606.01031","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.01031","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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Audio-driven":[0],"talking-head":[1],"generation":[2],"has":[3],"advanced":[4],"rapidly,":[5],"yet":[6],"existing":[7],"evaluation":[8,75,106,138],"protocols":[9],"mainly":[10],"rely":[11],"on":[12,167],"frame-wise":[13,137],"metrics":[14,49,197],"that":[15,74,98,136,194],"assume":[16],"strict":[17],"temporal":[18,114,123],"correspondence":[19],"between":[20,163,215],"generated":[21],"and":[22,42,65,160,185,210,223],"reference":[23],"videos.":[24],"This":[25],"assumption":[26],"does":[27],"not":[28],"match":[29],"speech-driven":[30],"facial":[31],"motion,":[32],"which":[33],"naturally":[34],"includes":[35],"slight":[36],"timing":[37,53,158,202],"shifts,":[38],"different":[39],"speaking":[40],"speeds,":[41],"stylistic":[43],"variations.":[44],"As":[45],"a":[46,84,94,143,173],"result,":[47],"conventional":[48],"may":[50],"treat":[51],"harmless":[52],"differences":[54],"as":[55,83,142,219],"quality":[56],"errors,":[57],"making":[58],"it":[59],"harder":[60],"to":[61,121,157,201],"fairly":[62],"compare":[63],"methods":[64,178],"understand":[66],"their":[67],"trade-offs.":[68],"In":[69],"this":[70,168],"work,":[71],"we":[72,171],"argue":[73],"of":[76,176],"dynamic":[77],"generative":[78],"models":[79],"should":[80],"be":[81,140],"formulated":[82],"sequence-alignment":[85],"problem":[86],"rather":[87],"than":[88],"independent":[89],"frame":[90],"comparison.":[91],"We":[92,134],"introduce":[93],"unified":[95],"sequence-level":[96,150],"reformulation":[97],"integrates":[99],"Soft":[100],"Dynamic":[101],"Time":[102],"Warping":[103],"into":[104],"established":[105],"pipelines.":[107],"By":[108],"aligning":[109],"feature":[110],"trajectories":[111],"while":[112,149],"preserving":[113],"order,":[115],"the":[116,127],"proposed":[117],"framework":[118],"provides":[119,152],"robustness":[120],"bounded":[122],"misalignments":[124],"without":[125],"altering":[126],"underlying":[128],"perceptual,":[129],"identity,":[130],"or":[131],"synchronization":[132,220],"encoders.":[133],"show":[135,193],"can":[139],"viewed":[141],"special":[144],"case":[145],"under":[146,188],"rigid":[147],"alignment,":[148],"alignment":[151],"improved":[153],"stability,":[154],"lower":[155],"sensitivity":[156],"differences,":[159,203],"clearer":[161],"separation":[162],"modeling":[164,216],"paradigms.":[165],"Building":[166],"principled":[169],"formulation,":[170],"conduct":[172],"large-scale":[174],"benchmark":[175],"20":[177],"across":[179,208],"seven":[180],"datasets":[181],"spanning":[182],"canonical,":[183],"in-the-wild,":[184],"style-diverse":[186],"scenarios":[187],"standardized":[189],"protocols.":[190],"Extensive":[191],"experiments":[192],"temporally":[195],"aligned":[196],"are":[198],"more":[199,205],"robust":[200],"provide":[204],"consistent":[206],"results":[207],"datasets,":[209],"better":[211],"reveal":[212],"systematic":[213],"trade-offs":[214],"paradigms,":[217],"such":[218],"versus":[221,225],"realism":[222],"expressiveness":[224],"stability.":[226]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-03T00:00:00"}