{"id":"W4407561023","doi":"10.3390/app15042002","title":"Speaker Diarization: A Review of Objectives and Methods","year":2025,"lang":"en","type":"review","venue":"Applied Sciences","topic":"Speech Recognition and Synthesis","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Speaker diarisation; Computer science; Speech recognition; Speaker recognition","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002033911,0.000209941,0.001137432,0.0002837904,0.0001336214,0.0001010221,0.0009841542,0.00008872357,0.00005295006],"category_scores_gemma":[0.0003619236,0.0001461579,0.0001688143,0.002027708,0.0003117578,0.0001392378,0.0003145258,0.0001044029,0.00001364581],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001380482,"about_ca_system_score_gemma":0.0004445219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001662558,"about_ca_topic_score_gemma":4.92084e-7,"domain_scores_codex":[0.9981904,0.0003061462,0.0004745526,0.0005838399,0.0002810898,0.0001639497],"domain_scores_gemma":[0.9978654,0.001365389,0.0003094325,0.0003506689,0.0000564135,0.00005274288],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[5.882835e-8,0.000007764287,1.356088e-7,0.02588759,0.00001300977,3.424667e-7,0.00001825061,6.522261e-9,3.903749e-7,0.03541624,0.0001591626,0.9384971],"study_design_scores_gemma":[0.00002981516,0.00001499511,0.000001669865,0.06153698,0.0001568708,0.00001466011,0.00001342057,0.00002830961,0.00005071706,0.003674166,0.9342306,0.000247804],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[8.305959e-9,0.8396835,0.09242075,0.00006468382,0.0001317011,0.0004345792,0.000003225882,0.00003771335,0.06722379],"genre_scores_gemma":[1.174552e-7,0.7692975,0.2302376,0.0002410346,0.00001607951,0.00007432755,0.000001462615,0.000002876972,0.0001289797],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9382492,"threshold_uncertainty_score":0.5960147,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05587897824479983,"score_gpt":0.4048335960937901,"score_spread":0.3489546178489903,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}