{"id":"W4412996470","doi":"10.14569/ijacsa.2025.0160726","title":"Speech Emotion Recognition from Audio Data Using LSTM Model","year":2025,"lang":"en","type":"article","venue":"International Journal of Advanced Computer Science and Applications","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Speech recognition; Emotion recognition; Artificial intelligence; Natural language processing","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":[0.0004690331,0.00009315459,0.0001212187,0.000363944,0.0002268988,0.0005026095,0.002617939,0.00002768268,0.000001430087],"category_scores_gemma":[0.00005200438,0.00008755192,0.00002760459,0.0006611098,0.0001361424,0.003088973,0.0007469798,0.0001334341,0.000002924622],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001142388,"about_ca_system_score_gemma":0.0005094586,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005529305,"about_ca_topic_score_gemma":0.00000189819,"domain_scores_codex":[0.9985237,0.00001256818,0.000350752,0.0003857899,0.0005830987,0.0001441246],"domain_scores_gemma":[0.9978739,0.00006156667,0.0003057704,0.0004059803,0.001272632,0.00008015387],"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":[0.000005208638,0.00004696845,0.00006437172,0.000002297064,0.00001717358,0.000003433042,0.00005711748,0.006229623,0.02276704,0.001136843,0.00008952594,0.9695804],"study_design_scores_gemma":[0.0004369271,0.00002073385,0.000510751,0.0001511969,0.00001399014,0.00006582614,0.00003010401,0.8682457,0.03420162,0.09443097,0.001760121,0.0001321078],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05267936,0.0001655496,0.94478,0.001592398,0.0005002999,0.0000833861,0.00001459666,0.0000259826,0.000158423],"genre_scores_gemma":[0.1932287,0.00009384896,0.8055646,0.000817451,0.0002737539,0.000002635799,0.000006987359,0.000002850649,0.000009185625],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9694483,"threshold_uncertainty_score":0.4864827,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04248749141003563,"score_gpt":0.3368987048711981,"score_spread":0.2944112134611625,"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."}}