{"id":"W4409088611","doi":"10.1515/comp-2025-0023","title":"Speech emotion recognition using long-term average spectrum","year":2025,"lang":"en","type":"article","venue":"Open Computer Science","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Term (time); Speech recognition; Psychology; Business; Audiology; Computer science; Medicine","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007130501,0.0001187846,0.0001354565,0.0003029398,0.0004042475,0.0005418214,0.0006944893,0.00006408813,0.001097526],"category_scores_gemma":[0.00001166728,0.0001201966,0.00004271974,0.0009412108,0.0001714158,0.0006838038,0.0003979034,0.0001392551,0.0006250516],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001076291,"about_ca_system_score_gemma":0.0001185041,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001177018,"about_ca_topic_score_gemma":0.00003122,"domain_scores_codex":[0.9985909,0.00009830725,0.0002220347,0.0005765601,0.0001959956,0.0003161656],"domain_scores_gemma":[0.9993334,0.00002775809,0.00009245956,0.0003494232,0.0001171942,0.00007971691],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00003250925,0.0003004252,0.003230632,0.00001833353,0.00002138807,0.00005191118,0.0004886911,0.00003357967,0.002714267,0.0015399,0.0009386573,0.9906297],"study_design_scores_gemma":[0.004997441,0.0005926049,0.8879163,0.001229225,0.00009590801,0.0007495746,0.0001483025,0.05025047,0.03029314,0.02083068,0.001585274,0.001311034],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5706505,0.00001131166,0.3761046,0.0003866951,0.003980218,0.0004090219,0.000003682026,0.00005765423,0.0483964],"genre_scores_gemma":[0.977003,0.000005984446,0.01916683,0.001371286,0.0002222003,0.000008752562,0.00001969858,0.000008722318,0.002193559],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9893187,"threshold_uncertainty_score":0.9998156,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07108019965778413,"score_gpt":0.3682452389487111,"score_spread":0.297165039290927,"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."}}