{"id":"W4416751125","doi":"10.1109/icrito66076.2025.11241506","title":"RBi-LSTM Based CNN Model for Speech Emotion Recognition","year":2025,"lang":"","type":"article","venue":"","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mel-frequency cepstrum; Convolutional neural network; Residual; Feature extraction; Test set; Set (abstract data type); Representation (politics); Artificial neural network; Feature (linguistics); 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":[0.0002191821,0.0008566697,0.000426727,0.0002584454,0.0001775534,0.0004350352,0.001087759,0.0006057523,0.005510988],"category_scores_gemma":[0.0004404568,0.0002763839,0.0005539028,0.0003366948,0.0001650352,0.0007367543,0.0003443057,0.001067309,0.002988365],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000753686,"about_ca_system_score_gemma":0.0006218164,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01268431,"about_ca_topic_score_gemma":0.01991562,"domain_scores_codex":[0.99989,0.000009976966,0.000005826999,0.00004519571,0.00002372924,0.000025308],"domain_scores_gemma":[0.9999226,0.00001565872,0.00000654099,0.000009822111,0.00004011495,0.000005117198],"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":[0.0004000767,0.0002137651,0.001371249,0.000311785,0.0001973101,0.0002482164,0.0000967117,0.414177,0.08546601,0.005731271,0.02137017,0.4704165],"study_design_scores_gemma":[0.000004233148,0.00003026461,0.0003266064,0.000007709345,0.0000176205,0.00002451771,0.000006593347,0.9912719,0.00621763,0.0006335257,0.001452407,0.000006957285],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09817713,0.003757393,0.8560228,0.0009266061,0.0007906125,0.0001432777,0.003079002,0.01358287,0.0235202],"genre_scores_gemma":[0.8258117,0.001486311,0.1295419,0.0004435992,0.000123856,0.0002350769,0.004552447,0.0003284543,0.03747683],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01268431,"threshold_uncertainty_score":0.02522099,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08459670452632377,"score_gpt":0.3561419061146349,"score_spread":0.2715452015883111,"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."}}