{"id":"W2615564100","doi":"10.1016/j.forsciint.2017.05.007","title":"Empirical test of the performance of an acoustic-phonetic approach to forensic voice comparison under conditions similar to those of a real case","year":2017,"lang":"en","type":"article","venue":"Forensic Science International","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Division of Mathematical Sciences; Engineering and Physical Sciences Research Council; Australasian Speech Science and Technology Association; Australian Research Council; Australian Federal Police","keywords":"Formant; Reliability (semiconductor); Speech recognition; Computer science; Empirical research; Forensic science; Identity (music); Acoustics; Statistics; Mathematics; History","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009730722,0.0005581234,0.0003369527,0.001353051,0.0006502074,0.001017497,0.001051101,0.001907024,0.002312473],"category_scores_gemma":[0.06978671,0.000221463,0.0003821953,0.0006308053,0.001313291,0.001684809,0.002141414,0.0006766755,0.0008583835],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003522013,"about_ca_system_score_gemma":0.0003931404,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001171323,"about_ca_topic_score_gemma":0.001071985,"domain_scores_codex":[0.9930087,0.003847423,0.0006630592,0.001116902,0.001115201,0.0002486577],"domain_scores_gemma":[0.905719,0.07969188,0.002325488,0.004956653,0.006314338,0.0009927161],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.02743435,0.007335146,0.3494484,0.001649533,0.001179949,0.001468481,0.006734588,0.09215137,0.2307683,0.00379261,0.001785043,0.2762522],"study_design_scores_gemma":[0.0005798465,0.02109169,0.4815322,0.0001658105,0.0005766959,0.004134174,0.006600501,0.3969192,0.08247299,0.002930691,0.002745174,0.0002509368],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9797148,0.0001429894,0.01729508,0.00006609449,0.00003159113,0.00007871026,0.0001503868,0.00006775848,0.002452685],"genre_scores_gemma":[0.9905357,0.00003845101,0.008804344,0.00001903285,0.00001713452,0.00003093193,0.00022694,0.00001349559,0.0003139383],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009730722,"threshold_uncertainty_score":0.05146164,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05835509408774393,"score_gpt":0.362335162749972,"score_spread":0.3039800686622281,"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."}}