{"id":"W4410057347","doi":"10.22214/ijraset.2025.70092","title":"Audio Aura - Speech Emotion Recognition System","year":2025,"lang":"en","type":"article","venue":"International Journal for Research in Applied Science and Engineering Technology","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Aura; Speech recognition; Computer science; 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":[0.0003717891,0.001082119,0.0006882154,0.0006225143,0.0002836837,0.0006438362,0.0007450769,0.000636786,0.01076001],"category_scores_gemma":[0.000782206,0.0001647477,0.0003985551,0.0002094413,0.0001472655,0.0005821843,0.0007405596,0.0004821389,0.007980185],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003960121,"about_ca_system_score_gemma":0.0003397434,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002174266,"about_ca_topic_score_gemma":0.001984105,"domain_scores_codex":[0.9996203,0.00003714611,0.00003555619,0.0001413686,0.0001186728,0.00004694549],"domain_scores_gemma":[0.9997829,0.00002799453,0.00001650964,0.00002765261,0.0001193854,0.0000254915],"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":[0.004051636,0.0005310616,0.006735742,0.00079234,0.0002437695,0.001135024,0.0001661666,0.007713203,0.2170341,0.001304482,0.1543435,0.6059489],"study_design_scores_gemma":[0.000472231,0.001527745,0.01881772,0.0001093731,0.0003886682,0.00196477,0.0002476883,0.6363688,0.2534018,0.002658612,0.08382285,0.0002198543],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2828007,0.005912161,0.3201201,0.001383966,0.002777862,0.00156483,0.04123586,0.2900513,0.05415319],"genre_scores_gemma":[0.7952239,0.0008039859,0.1151264,0.001277111,0.000444348,0.0008892378,0.04923852,0.0009732424,0.03602329],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01076001,"threshold_uncertainty_score":0.03599584,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04380399234874722,"score_gpt":0.363387464823246,"score_spread":0.3195834724744988,"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."}}