{"id":"W4384517870","doi":"10.1109/cbms58004.2023.00241","title":"Voice Emotion Recognition Based on Color Histogram Features","year":2023,"lang":"en","type":"article","venue":"","topic":"Music and Audio Processing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Computer science; Speech recognition; Spectrogram; Set (abstract data type); Speaker recognition; Histogram; Facial expression; Subject (documents); Identification (biology); Emotion recognition; Speech processing; Artificial intelligence; Natural language processing; Image (mathematics)","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":[0.0003109711,0.0005505562,0.0005411358,0.001521599,0.0001748152,0.0006583997,0.0003770269,0.0004086769,0.001957611],"category_scores_gemma":[0.001128342,0.0001027922,0.0005606106,0.0006439302,0.0001996773,0.0005872706,0.0003302167,0.000364432,0.001244124],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003002686,"about_ca_system_score_gemma":0.0002412908,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003317644,"about_ca_topic_score_gemma":0.002576483,"domain_scores_codex":[0.9995485,0.00004375319,0.00002651633,0.0001132844,0.0001847319,0.00008314458],"domain_scores_gemma":[0.9994443,0.0001023723,0.00004885099,0.00003597326,0.0003425727,0.00002591544],"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":[0.001171713,0.0001612619,0.01178235,0.000264788,0.00011561,0.0003036435,0.0001622764,0.00530316,0.2664227,0.0007559211,0.01088666,0.7026699],"study_design_scores_gemma":[0.0001357009,0.0008502417,0.1881916,0.00009331326,0.0004148397,0.00161045,0.0009221567,0.4862104,0.2934317,0.002238626,0.02568178,0.0002192825],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4719194,0.004114239,0.4963579,0.0004514455,0.0008800356,0.0005397616,0.004474004,0.007991553,0.0132716],"genre_scores_gemma":[0.9168018,0.001135123,0.07195204,0.0001642709,0.0002531486,0.0002120347,0.003487183,0.0001783681,0.005816114],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003317644,"threshold_uncertainty_score":0.006596684,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03198062412692756,"score_gpt":0.2566569029547336,"score_spread":0.2246762788278061,"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."}}