{"id":"https://openalex.org/W7161731538","doi":"https://doi.org/10.48550/arxiv.2605.17652","title":"Beyond Transcripts: Iterative Peer-Editing with Audio Unlocks High-Quality Human Summaries of Conversational Speech","display_name":"Beyond Transcripts: Iterative Peer-Editing with Audio Unlocks High-Quality Human Summaries of Conversational Speech","publication_year":2026,"publication_date":"2026-05-17","ids":{"openalex":"https://openalex.org/W7161731538","doi":"https://doi.org/10.48550/arxiv.2605.17652"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.17652","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.17652","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.2605.17652","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5095094640","display_name":"Kaavya Chaparala","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chaparala, Kaavya","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040324682","display_name":"Thomas Thebaud","orcid":"https://orcid.org/0000-0001-8953-7872"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Thebaud, Thomas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132807342","display_name":"Jesus Villalba Lopez","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"L\u00f3pez, Jes\u00fas Villalba","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136460672","display_name":"Laureano Moro-Velazquez","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Moro-Velazquez, Laureano","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041825272","display_name":"Peter Viechnicki","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Viechnicki, Peter","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136473459","display_name":"Najim Dehak","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dehak, Najim","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":0.5680999755859375,"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":0.5680999755859375,"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/T12031","display_name":"Speech and dialogue systems","score":0.15139999985694885,"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/T13274","display_name":"Expert finding and Q&A systems","score":0.027499999850988388,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/annotation","display_name":"Annotation","score":0.6748999953269958},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6258999705314636},{"id":"https://openalex.org/keywords/workflow","display_name":"Workflow","score":0.6162999868392944},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.46000000834465027},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.45669999718666077},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.33640000224113464},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.31349998712539673}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8343999981880188},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.6748999953269958},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6258999705314636},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.6162999868392944},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5867000222206116},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49070000648498535},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.46000000834465027},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.45669999718666077},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.43619999289512634},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.39100000262260437},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.33640000224113464},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.31349998712539673},{"id":"https://openalex.org/C59656382","wikidata":"https://www.wikidata.org/wiki/Q191536","display_name":"Conjunction (astronomy)","level":2,"score":0.30630001425743103},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.29260000586509705},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.2913999855518341},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.28119999170303345},{"id":"https://openalex.org/C2779982483","wikidata":"https://www.wikidata.org/wiki/Q6094420","display_name":"Iterative refinement","level":2,"score":0.2718000113964081},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.2615000009536743},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2572000026702881},{"id":"https://openalex.org/C2777200299","wikidata":"https://www.wikidata.org/wiki/Q52943","display_name":"Conversation","level":2,"score":0.2540000081062317}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.17652","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.17652","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.2605.17652","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.17652","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":[{"score":0.5092954039573669,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"There":[0],"are":[1,100,113,174],"not":[2],"enough":[3],"established":[4],"benchmarks":[5,14,90,156],"for":[6,152],"the":[7,41,71,74,84,153],"task":[8],"fo":[9],"speech":[10],"summarization.":[11],"Creating":[12],"new":[13],"demands":[15],"human":[16,55,62,66,85,150],"annotation,":[17],"as":[18,135,137],"LLMs":[19],"could":[20],"embed":[21],"systemic":[22],"errors":[23],"and":[24,40,116,141,161],"bias":[25],"into":[26],"datasets.":[27],"We":[28,60,81,108],"test":[29],"ten":[30],"annotation":[31],"workflows":[32],"varying":[33],"input":[34],"modality":[35],"(audio,":[36],"transcript,":[37],"or":[38,46],"both)":[39],"inclusion":[42],"of":[43,73,155],"editing":[44],"(self":[45],"peer-editing)":[47],"to":[48,57,65,69,95,133],"investigate":[49],"potential":[50],"quality":[51],"tradeoffs":[52],"from":[53],"using":[54],"annotators":[56,151],"summarize":[58],"audio.":[59],"compare":[61,83],"audio-based":[63,111,131],"summaries":[64,68,99,112,132],"transcript-based":[67],"track":[70],"impact":[72],"different":[75],"information":[76],"modalities":[77],"on":[78],"summary":[79],"quality.":[80],"also":[82],"outputs":[86],"against":[87],"four":[88],"LLM":[89,142],"(three":[91],"text,":[92],"one":[93],"audio)":[94],"examine":[96],"whether":[97],"human-written":[98],"less":[101,114],"informative":[102,115,136],"than":[103,119],"highly":[104],"fluent":[105],"automated":[106],"outputs.":[107],"find":[109],"that":[110],"more":[117],"compressed":[118],"transcript":[120,139],"summaries.":[121,143],"However,":[122],"iterative":[123,147],"peer-editing":[124,148],"with":[125],"audio":[126],"mitigates":[127],"this":[128],"difference,":[129],"enabling":[130],"be":[134],"their":[138],"counterparts":[140],"These":[144],"findings":[145],"validate":[146],"among":[149],"creation":[154],"informed":[157],"by":[158],"both":[159],"lexical":[160],"prosodic":[162],"information.":[163],"This":[164],"enables":[165],"crucial":[166],"dataset":[167],"collection":[168],"even":[169],"in":[170],"setting":[171],"where":[172],"transcripts":[173],"unavailable.":[175]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-20T00:00:00"}