{"id":"W3164145231","doi":"10.1109/ssd52085.2021.9429403","title":"Speaker Identification for Disguised Voices Based on Modified SVM Classifier","year":2021,"lang":"en","type":"article","venue":"","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Support vector machine; Computer science; Speech recognition; Naive Bayes classifier; Perceptron; Classifier (UML); Speaker identification; Artificial intelligence; Multilayer perceptron; Pattern recognition (psychology); Speaker recognition; Identification (biology); Radial basis function; Speaker diarisation; Arabic; Natural language processing; Machine learning; Artificial neural network","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008189072,0.0004831248,0.0006846482,0.0008760673,0.0002725724,0.0006417741,0.000439797,0.0006164943,0.001403861],"category_scores_gemma":[0.001701022,0.00011356,0.0004197513,0.0003475257,0.0001625168,0.0007869614,0.0003984175,0.0005337931,0.0009946437],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001969109,"about_ca_system_score_gemma":0.000252162,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000966951,"about_ca_topic_score_gemma":0.0009869777,"domain_scores_codex":[0.9991653,0.0001697933,0.00008013394,0.0001928019,0.000303891,0.00008812473],"domain_scores_gemma":[0.9989235,0.0003229593,0.00009837637,0.00009426172,0.0005198778,0.00004095524],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0009092367,0.0002627017,0.01188911,0.0001973949,0.0001673934,0.0003173283,0.0001664281,0.02121955,0.183942,0.0008166972,0.002356531,0.7777556],"study_design_scores_gemma":[0.00002133491,0.0004558159,0.01380495,0.00002746727,0.00008393714,0.000678062,0.0001608112,0.9069178,0.07471787,0.0005855642,0.002500574,0.00004587469],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4332211,0.001200865,0.5597632,0.0002402496,0.0003849755,0.0001167242,0.0002973343,0.001969396,0.002806228],"genre_scores_gemma":[0.8981158,0.0002928011,0.09845681,0.00006602822,0.00006911526,0.00004884386,0.0005235345,0.00004354068,0.00238351],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001403861,"threshold_uncertainty_score":0.004696429,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03181875860152367,"score_gpt":0.2798014935487919,"score_spread":0.2479827349472682,"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."}}