{"id":"W4408303417","doi":"10.3126/jacem.v10i1.76324","title":"CNN-Transformer Based Speech Emotion Detection","year":2025,"lang":"en","type":"article","venue":"Journal of Advanced College of Engineering and Management","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Transformer; Speech recognition; Computer science; Emotion detection; Natural language processing; Artificial intelligence; Electrical engineering; Engineering; Emotion recognition; Voltage","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":[0.0005171953,0.001158942,0.0004662577,0.0004958076,0.0002037084,0.00048346,0.000743355,0.0004611982,0.003194308],"category_scores_gemma":[0.0009855969,0.0002504123,0.0006493398,0.0002804585,0.000182185,0.0008693712,0.0006319492,0.0008171273,0.00184961],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006078439,"about_ca_system_score_gemma":0.0003881253,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004528232,"about_ca_topic_score_gemma":0.006716449,"domain_scores_codex":[0.9996152,0.00004315056,0.00001586206,0.0001410938,0.00009540185,0.000089188],"domain_scores_gemma":[0.9997392,0.0000501531,0.00001744084,0.00003374024,0.0001427318,0.00001663796],"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":[0.001174772,0.0004507564,0.007318226,0.00022278,0.0002277557,0.0003293147,0.0001271555,0.05988633,0.1260796,0.001777773,0.0119808,0.7904247],"study_design_scores_gemma":[0.00001879791,0.0002185035,0.005084917,0.00001480976,0.00009143315,0.0001824722,0.00007057689,0.9415833,0.04866463,0.0008646498,0.003186211,0.00001959625],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4618583,0.002538778,0.4966229,0.000577116,0.001135461,0.0004688216,0.002179492,0.009261979,0.02535718],"genre_scores_gemma":[0.9156049,0.0004630341,0.06478747,0.0002467556,0.00009040104,0.0001276342,0.002927239,0.0001224824,0.01563009],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004528232,"threshold_uncertainty_score":0.01068598,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003251466268921647,"score_gpt":0.2048655346664257,"score_spread":0.2016140683975041,"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."}}