{"id":"https://openalex.org/W7160259070","doi":"https://doi.org/10.48550/arxiv.2605.02223","title":"Toward Fine-Grained Speech Inpainting Forensics:A Dataset, Method, and Metric for Multi-Region Tampering Localization","display_name":"Toward Fine-Grained Speech Inpainting Forensics:A Dataset, Method, and Metric for Multi-Region Tampering Localization","publication_year":2026,"publication_date":"2026-05-04","ids":{"openalex":"https://openalex.org/W7160259070","doi":"https://doi.org/10.48550/arxiv.2605.02223"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.02223","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.02223","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.2605.02223","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135324858","display_name":"Tung Vu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Vu, Tung","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135405680","display_name":"Yen Nguyen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nguyen, Yen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088039595","display_name":"Hai V. Nguyen","orcid":"https://orcid.org/0000-0002-2578-170X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nguyen, Hai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135368397","display_name":"Cuong The Pham","orcid":"https://orcid.org/0000-0001-5158-4526"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pham, Cuong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5124960734","display_name":"Cong Tran","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tran, Cong","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":0.3855000138282776,"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":0.3855000138282776,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.32120001316070557,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.06369999796152115,"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/metric","display_name":"Metric (unit)","score":0.620199978351593},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.6004999876022339},{"id":"https://openalex.org/keywords/utterance","display_name":"Utterance","score":0.5426999926567078},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.46070000529289246},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4587000012397766},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.4505999982357025},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.446399986743927},{"id":"https://openalex.org/keywords/identity","display_name":"Identity (music)","score":0.4404999911785126},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4165000021457672},{"id":"https://openalex.org/keywords/identifier","display_name":"Identifier","score":0.4065999984741211}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8052999973297119},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.620199978351593},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6173999905586243},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.6004999876022339},{"id":"https://openalex.org/C2775852435","wikidata":"https://www.wikidata.org/wiki/Q258403","display_name":"Utterance","level":2,"score":0.5426999926567078},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.46070000529289246},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4587000012397766},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.4505999982357025},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.446399986743927},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.4404999911785126},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4165000021457672},{"id":"https://openalex.org/C154504017","wikidata":"https://www.wikidata.org/wiki/Q853614","display_name":"Identifier","level":2,"score":0.4065999984741211},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4032000005245209},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3887999951839447},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3878999948501587},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.36629998683929443},{"id":"https://openalex.org/C11727466","wikidata":"https://www.wikidata.org/wiki/Q1628157","display_name":"Inpainting","level":3,"score":0.34549999237060547},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.33340001106262207},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.33079999685287476},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3292999863624573},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.32850000262260437},{"id":"https://openalex.org/C41065033","wikidata":"https://www.wikidata.org/wiki/Q2825412","display_name":"Adversary","level":2,"score":0.3165000081062317},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.3077999949455261},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.29600000381469727},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.295199990272522},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.2856999933719635},{"id":"https://openalex.org/C207347870","wikidata":"https://www.wikidata.org/wiki/Q371174","display_name":"Gesture","level":2,"score":0.2842999994754791},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.27950000762939453},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.27810001373291016},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.27129998803138733},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.26570001244544983},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2646999955177307},{"id":"https://openalex.org/C74050887","wikidata":"https://www.wikidata.org/wiki/Q848368","display_name":"Rotation (mathematics)","level":2,"score":0.2637999951839447},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.2619999945163727},{"id":"https://openalex.org/C87619178","wikidata":"https://www.wikidata.org/wiki/Q126002","display_name":"Concatenation (mathematics)","level":2,"score":0.2533000111579895}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.02223","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.02223","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.2605.02223","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.02223","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":[{"score":0.6507270336151123,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Recent":[0],"advances":[1],"in":[2,55,213],"voice":[3,105],"cloning":[4],"and":[5,57,103,135,168,217,221],"text-to-speech":[6],"synthesis":[7],"have":[8],"made":[9],"partial":[10,175],"speech":[11,192],"manipulation":[12],"-":[13,33],"where":[14,201],"an":[15,22,34],"adversary":[16],"replaces":[17],"a":[18,52,66,83,123,153],"few":[19],"words":[20],"within":[21],"utterance":[23],"to":[24,138,198],"alter":[25],"its":[26],"meaning":[27],"while":[28],"preserving":[29],"the":[30,218],"speaker's":[31],"identity":[32],"increasingly":[35],"realistic":[36],"threat.":[37],"Existing":[38],"audio":[39],"deepfake":[40,184],"detection":[41],"benchmarks":[42],"focus":[43],"on":[44,158,189],"utterance-level":[45,186],"binary":[46],"classification":[47,130],"or":[48],"single-region":[49],"tampering,":[50],"leaving":[51],"critical":[53],"gap":[54,71],"detecting":[56],"localizing":[58],"multiple":[59],"inpainted":[60,93],"segments":[61,95],"whose":[62],"count":[63,166],"is":[64,206],"unknown":[65],"priori.":[67],"We":[68],"address":[69],"this":[70,214],"with":[72,90,107,131],"three":[73],"contributions.":[74],"First,":[75],"we":[76,117,150],"introduce":[77],"MIST":[78,199],"(Multiregion":[79],"Inpainting":[80],"Speech":[81],"Tampering),":[82],"large-scale":[84],"multilingual":[85],"dataset":[86],"spanning":[87],"6":[88],"languages":[89],"1-3":[91],"independently":[92],"word-level":[94],"per":[96],"utterance,":[97],"generated":[98],"via":[99],"LLM-guided":[100],"semantic":[101],"replacement":[102],"neural":[104],"cloning,":[106],"fake":[108,196],"content":[109,205],"constituting":[110],"only":[111,202],"2-7%":[112,203],"of":[113,146,204],"each":[114],"utterance.":[115],"Second,":[116],"propose":[118],"ISA":[119,208],"(Iterative":[120],"Segment":[121],"Analysis),":[122],"backbone-agnostic":[124],"framework":[125],"that":[126,162,174],"performs":[127],"coarse-to-fine":[128],"sliding-window":[129],"gap-tolerant":[132],"region":[133,165],"proposal":[134],"boundary":[136],"refinement":[137],"recover":[139],"all":[140],"tampered":[141],"regions":[142],"without":[143],"prior":[144],"knowledge":[145],"their":[147],"count.":[148],"Third,":[149],"define":[151],"SF1@tau,":[152],"segment-level":[154],"F1":[155],"metric":[156],"based":[157],"temporal":[159],"IoU":[160],"matching":[161],"jointly":[163],"evaluates":[164],"accuracy":[167],"localization":[169],"precision.":[170],"Zero-shot":[171],"evaluation":[172,222],"reveals":[173],"inpainting":[176],"at":[177],"word":[178],"granularity":[179],"remains":[180],"unsolved":[181],"by":[182],"existing":[183],"detectors:":[185],"classifiers":[187],"trained":[188],"fully":[190],"synthesized":[191],"assign":[193],"near":[194],"zero":[195],"probability":[197],"utterances":[200],"manipulated.":[207],"consistently":[209],"outperforms":[210],"non-iterative":[211],"baselines":[212],"challenging":[215],"setting,":[216],"dataset,":[219],"code,":[220],"toolkit":[223],"are":[224],"publicly":[225],"released.":[226]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-05-06T00:00:00"}
