{"id":"W4312330812","doi":"10.56828/jser.2022.1.1.3","title":"Voiceprint Recognition based on Machine Learning Methods","year":2022,"lang":"en","type":"article","venue":"Journal of Science and Engineering Research","topic":"Speech Recognition and Synthesis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Computer science; Speech recognition; Speaker recognition; Identification (biology); Feature (linguistics); Biometrics; Task (project management); Artificial intelligence; Pattern recognition (psychology); Engineering","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":[0.01649034,0.00005511986,0.00009860704,0.001215449,0.000577535,0.0001994841,0.0006459425,0.00001363766,0.00007700672],"category_scores_gemma":[0.00211916,0.00004752538,0.0000348848,0.001619202,0.0001152098,0.0003549737,0.0002429517,0.0007840529,0.000006001392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001616871,"about_ca_system_score_gemma":0.0002129463,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006102657,"about_ca_topic_score_gemma":1.097756e-7,"domain_scores_codex":[0.9977661,0.0002223412,0.0001747969,0.0001701077,0.001403417,0.0002632306],"domain_scores_gemma":[0.9985683,0.0006415937,0.00005827098,0.000125477,0.0004487244,0.0001576562],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002343594,0.00007769483,0.0001265289,0.00001546018,0.000005487766,0.00006158213,0.0004311661,0.0146838,0.06018957,0.0004649814,0.0001013199,0.9238189],"study_design_scores_gemma":[0.0002051965,0.0004968746,0.001366263,0.00003245389,0.00000151687,0.0001489186,0.0002061393,0.9712716,0.01773708,0.0004500644,0.007998643,0.00008528963],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.364557,0.0003052965,0.6250222,0.005510103,0.001063507,0.0001928217,0.000002315348,0.00009263968,0.003254116],"genre_scores_gemma":[0.7777312,0.00003830703,0.2220219,0.0001057393,0.0000483941,0.00000730971,1.585774e-7,0.000005510614,0.00004147836],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9565877,"threshold_uncertainty_score":0.5715256,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1059199732446794,"score_gpt":0.3791078615026312,"score_spread":0.2731878882579518,"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."}}