{"id":"W4295919040","doi":"10.1109/ic3sis54991.2022.9885578","title":"Speech Emotion Recognition Using Bagged Support Vector Machines","year":2022,"lang":"en","type":"article","venue":"2022 International Conference on Computing, Communication, Security and Intelligent Systems (IC3SIS)","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Support vector machine; Set (abstract data type); Hidden Markov model; Artificial neural network; Estimator; Emotion recognition; Voice activity detection; Mixture model; Kernel (algebra); Pattern recognition (psychology)","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":[0.001181416,0.0007720668,0.0007662344,0.0007986698,0.0002825769,0.0009464506,0.0006695767,0.0007241423,0.001181328],"category_scores_gemma":[0.002815974,0.0002376548,0.0007663804,0.0005313896,0.0001699367,0.00127249,0.0006864893,0.001274536,0.0009763959],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002335312,"about_ca_system_score_gemma":0.0002391092,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001413386,"about_ca_topic_score_gemma":0.00120393,"domain_scores_codex":[0.999037,0.0002566602,0.000079514,0.0002495543,0.0002465557,0.0001307234],"domain_scores_gemma":[0.9989267,0.0004109815,0.00008624261,0.0001223453,0.0004131368,0.00004065042],"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":[0.0004739288,0.0003139339,0.00499519,0.00009264277,0.0002617466,0.0001359657,0.0001749883,0.08774008,0.03057309,0.0008169438,0.002782333,0.8716391],"study_design_scores_gemma":[0.000006836932,0.0001479495,0.002395332,0.00001102869,0.00002981878,0.00006471401,0.00006049684,0.9849678,0.0105559,0.001072208,0.0006698881,0.00001806297],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1989554,0.001248241,0.7939885,0.0002983835,0.0003377912,0.00007881664,0.0003517085,0.00328482,0.001456222],"genre_scores_gemma":[0.8819786,0.0002833542,0.114968,0.00008466129,0.00008304659,0.00007236825,0.0007095305,0.00006620042,0.001754253],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001413386,"threshold_uncertainty_score":0.006248057,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.108398791139649,"score_gpt":0.3543102198666948,"score_spread":0.2459114287270457,"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."}}