{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003046238,0.00007271823,0.00009595038,0.003105643,0.0002759752,0.0005049441,0.001362119,0.00007891207,6.712035e-7],"category_scores_gemma":[0.0004174728,0.00006925082,0.00001623333,0.002122033,0.0001775947,0.0003853988,0.0003365648,0.0004480706,0.000005209573],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000511852,"about_ca_system_score_gemma":0.0002784276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002995951,"about_ca_topic_score_gemma":0.000001104488,"domain_scores_codex":[0.9984733,0.000007562762,0.0002134012,0.0002927146,0.0006054066,0.0004075579],"domain_scores_gemma":[0.9990185,0.00008641992,0.00004122056,0.0001369979,0.0006576367,0.0000592364],"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":[0.00001383863,0.00002222603,0.0001030447,0.00004106842,0.00001081823,0.00003538431,0.00004992933,0.0001682967,0.1184203,0.1035637,0.0001933468,0.7773781],"study_design_scores_gemma":[0.001606965,0.0001439591,0.000783911,0.00111132,0.000003562805,0.001030325,0.0008420399,0.1545331,0.6127451,0.216198,0.0106603,0.0003413259],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2628295,0.0002109292,0.7180393,0.01226494,0.002161758,0.0003881971,0.00000212117,0.000322689,0.003780477],"genre_scores_gemma":[0.9281052,0.0000419466,0.07167441,0.00003577599,0.00007087074,0.00004202613,5.182011e-7,0.000003690666,0.00002558502],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7770367,"threshold_uncertainty_score":0.4869187,"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."}}