{"id":"W4411600434","doi":"10.1109/icaiss61471.2025.11041993","title":"Multimodal Emotion Recognition: An Integrated Approach using Facial, Audio and Text Analysis","year":2025,"lang":"en","type":"article","venue":"","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Emotion recognition; Speech recognition; Facial recognition system; Natural language processing; Artificial intelligence; Human–computer interaction; Feature extraction","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":[0.0007316647,0.001134501,0.0007314584,0.001201512,0.0002440852,0.001008939,0.0007665966,0.0006715277,0.002658436],"category_scores_gemma":[0.001331908,0.0002429964,0.000904786,0.000561993,0.0002335014,0.001430638,0.0009862122,0.0006570679,0.001923425],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003700531,"about_ca_system_score_gemma":0.0002923582,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001874557,"about_ca_topic_score_gemma":0.002247845,"domain_scores_codex":[0.9994506,0.00008442777,0.00003507685,0.000198783,0.0001739874,0.00005713922],"domain_scores_gemma":[0.9996055,0.00007906683,0.00004826713,0.00004767202,0.0001954912,0.00002404687],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005644036,0.0002782317,0.004956789,0.0002370833,0.0001964116,0.0002660695,0.0002512363,0.01077156,0.1584549,0.0009658243,0.006579836,0.8164777],"study_design_scores_gemma":[0.00004204416,0.0007465598,0.02714661,0.0001392454,0.0004321233,0.0007308047,0.0006420744,0.8088598,0.1381112,0.005531022,0.01746815,0.0001503851],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0939059,0.001895174,0.888082,0.0007580849,0.0003391582,0.0003843208,0.001179131,0.0053808,0.008075343],"genre_scores_gemma":[0.609087,0.001775763,0.3717164,0.0005281537,0.0003335076,0.0004079772,0.002273317,0.0003570471,0.01352082],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002658436,"threshold_uncertainty_score":0.008893311,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06281451692226704,"score_gpt":0.3421319669777908,"score_spread":0.2793174500555238,"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."}}