{"id":"https://openalex.org/W7119547337","doi":"https://doi.org/10.48550/arxiv.2601.03684","title":"Domain Adaptation of the Pyannote Diarization Pipeline for Conversational Indonesian Audio","display_name":"Domain Adaptation of the Pyannote Diarization Pipeline for Conversational Indonesian Audio","publication_year":2026,"publication_date":"2026-01-07","ids":{"openalex":"https://openalex.org/W7119547337","doi":"https://doi.org/10.48550/arxiv.2601.03684"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2601.03684","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.03684","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":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.2601.03684","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5122370567","display_name":"Muhammad Daffa'i Rafi Prasetyo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Prasetyo, Muhammad Daffa'i Rafi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122349567","display_name":"Ramadhan Andika Putra","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Putra, Ramadhan Andika","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122358887","display_name":"Zaidan Naufal Ilmi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ilmi, Zaidan Naufal","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5066073372","display_name":"Kurniawati Azizah","orcid":"https://orcid.org/0000-0002-3217-7025"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Azizah, Kurniawati","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":0.9254999756813049,"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":0.9254999756813049,"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/T10863","display_name":"Voice and Speech Disorders","score":0.014000000432133675,"subfield":{"id":"https://openalex.org/subfields/2737","display_name":"Physiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.012400000356137753,"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/pipeline","display_name":"Pipeline (software)","score":0.802299976348877},{"id":"https://openalex.org/keywords/speaker-diarisation","display_name":"Speaker diarisation","score":0.7193999886512756},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.6026999950408936},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.5831000208854675},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5403000116348267},{"id":"https://openalex.org/keywords/nist","display_name":"NIST","score":0.5076000094413757},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.4997999966144562},{"id":"https://openalex.org/keywords/indonesian","display_name":"Indonesian","score":0.47110000252723694},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.42329999804496765}],"concepts":[{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.802299976348877},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7857000231742859},{"id":"https://openalex.org/C149838564","wikidata":"https://www.wikidata.org/wiki/Q7574248","display_name":"Speaker diarisation","level":3,"score":0.7193999886512756},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6873000264167786},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.6026999950408936},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.5831000208854675},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5403000116348267},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5149000287055969},{"id":"https://openalex.org/C111219384","wikidata":"https://www.wikidata.org/wiki/Q6954384","display_name":"NIST","level":2,"score":0.5076000094413757},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.4997999966144562},{"id":"https://openalex.org/C2779207338","wikidata":"https://www.wikidata.org/wiki/Q9240","display_name":"Indonesian","level":2,"score":0.47110000252723694},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.42329999804496765},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.387800008058548},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3833000063896179},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.375900000333786},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.33649998903274536},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.3312000036239624},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.3260999917984009},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3246000111103058},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3165000081062317},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.29670000076293945},{"id":"https://openalex.org/C2778915421","wikidata":"https://www.wikidata.org/wiki/Q3643177","display_name":"Performance improvement","level":2,"score":0.29600000381469727},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.27720001339912415},{"id":"https://openalex.org/C204201278","wikidata":"https://www.wikidata.org/wiki/Q1332614","display_name":"Voice activity detection","level":3,"score":0.2768999934196472},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.263700008392334},{"id":"https://openalex.org/C61328038","wikidata":"https://www.wikidata.org/wiki/Q3358061","display_name":"Speech processing","level":2,"score":0.2547000050544739},{"id":"https://openalex.org/C133892786","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker recognition","level":2,"score":0.2533000111579895},{"id":"https://openalex.org/C2779182362","wikidata":"https://www.wikidata.org/wiki/Q17126187","display_name":"Session (web analytics)","level":2,"score":0.251800000667572}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2601.03684","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.03684","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":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.2601.03684","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.03684","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"score":0.7030824422836304,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0],"study":[1],"presents":[2],"a":[3,25,44,50,72,116,121],"domain":[4],"adaptation":[5,85],"approach":[6],"for":[7],"speaker":[8],"diarization":[9,22],"targeting":[10],"conversational":[11],"Indonesian":[12],"audio.":[13],"We":[14],"address":[15],"the":[16,62,68,90,108,112,126],"challenge":[17],"of":[18,56,77,118],"adapting":[19],"an":[20],"English-centric":[21],"pipeline":[23],"to":[24,82,96],"low-resource":[26],"language":[27],"by":[28],"employing":[29],"synthetic":[30,57],"data":[31],"generation":[32],"using":[33],"neural":[34],"Text-to-Speech":[35],"technology.":[36],"Experiments":[37],"were":[38],"conducted":[39],"with":[40,89,115],"varying":[41],"training":[42],"configurations,":[43],"small":[45,91],"dataset":[46,52,92,110],"(171":[47],"samples)":[48],"and":[49,100,132],"large":[51],"containing":[53],"25":[54],"hours":[55],"speech.":[58],"Results":[59],"demonstrate":[60],"that":[61],"baseline":[63,127],"\\texttt{pyannote/segmentation-3.0}":[64],"model,":[65],"trained":[66,106],"on":[67,107],"AMI":[69],"Corpus,":[70],"achieves":[71,111],"Diarization":[73],"Error":[74],"Rate":[75],"(DER)":[76],"53.47\\%":[78],"when":[79],"applied":[80],"zero-shot":[81],"Indonesian.":[83],"Domain":[84],"significantly":[86],"improves":[87],"performance,":[88],"models":[93],"reducing":[94],"DER":[95,117],"34.31\\%":[97],"(1":[98],"epoch)":[99],"34.81\\%":[101],"(2":[102],"epochs).":[103],"The":[104],"model":[105],"25-hour":[109],"best":[113],"performance":[114],"29.24\\%,":[119],"representing":[120],"13.68\\%":[122],"absolute":[123],"improvement":[124],"over":[125],"while":[128],"maintaining":[129],"99.06\\%":[130],"Recall":[131],"87.14\\%":[133],"F1-Score.":[134]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-01-09T00:00:00"}