{"id":"W7143537207","doi":"10.1109/decon67170.2025.11448083","title":"Speech Emotion Recognition: A Human-Centric Framework with Enhanced Data Augmentation and Lightweight CNN","year":2025,"lang":"","type":"article","venue":"","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Feature (linguistics); Component (thermodynamics); Noise (video); Focus (optics)","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":[0.0002744379,0.0008270126,0.0003304629,0.0002451805,0.0001417002,0.0004292164,0.0008806185,0.0003659044,0.002596447],"category_scores_gemma":[0.0005049661,0.0001829056,0.0004319141,0.0001993608,0.0002087246,0.0006211453,0.0007089437,0.0006560067,0.001261026],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003602575,"about_ca_system_score_gemma":0.0003961363,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003922587,"about_ca_topic_score_gemma":0.007688939,"domain_scores_codex":[0.9998611,0.00001524186,0.000005401409,0.00005159532,0.00003921565,0.00002747869],"domain_scores_gemma":[0.9998989,0.00002031836,0.000009075015,0.00002165124,0.00004073428,0.000009264565],"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":[0.0005153602,0.0002574608,0.002229586,0.0001646478,0.000135724,0.0002169349,0.00009993579,0.08592948,0.1725506,0.003564555,0.01078639,0.7235493],"study_design_scores_gemma":[0.000012069,0.00010331,0.001407195,0.00001248642,0.00004267262,0.00008473032,0.0000222375,0.9637983,0.02846477,0.00165441,0.004384111,0.00001354677],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04837646,0.0006507005,0.9396626,0.0002901572,0.0001943518,0.0001130677,0.0003503944,0.00527936,0.005082855],"genre_scores_gemma":[0.7033689,0.0007451579,0.2771588,0.0004811854,0.0001434987,0.0002484288,0.001650896,0.0003106997,0.01589247],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003922587,"threshold_uncertainty_score":0.008685946,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05826125655485853,"score_gpt":0.3595346313012251,"score_spread":0.3012733747463666,"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."}}