{"id":"W4407854407","doi":"10.54097/hws7ck61","title":"Enhancing Emotion Recognition in Video Characters Through Multi-Modal Deep Learning Approaches","year":2025,"lang":"en","type":"article","venue":"Highlights in Science Engineering and Technology","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Modal; Emotion recognition; Computer science; Deep learning; Artificial intelligence; Psychology; Speech recognition; Cognitive psychology","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":[0.000567868,0.0009463176,0.0004388681,0.0004989138,0.0002261793,0.0007379713,0.0006299921,0.0004601991,0.001247395],"category_scores_gemma":[0.001245083,0.0001929804,0.0008949797,0.000298696,0.0002102356,0.0009444337,0.0008160656,0.0009925427,0.0005560255],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004654143,"about_ca_system_score_gemma":0.0002200018,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002286172,"about_ca_topic_score_gemma":0.004074574,"domain_scores_codex":[0.999744,0.00006429003,0.00001129251,0.00007857892,0.00005808996,0.00004374368],"domain_scores_gemma":[0.9997063,0.00009721824,0.00003073756,0.00002900681,0.0001135319,0.00002311101],"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":[0.0006531291,0.0006279036,0.007048724,0.0001681924,0.0003107281,0.0001900427,0.0002659117,0.2117482,0.09779599,0.002197719,0.005116188,0.6738772],"study_design_scores_gemma":[0.000004776852,0.00007498923,0.001565784,0.000007378612,0.00002879928,0.00003342857,0.00004373412,0.9894844,0.006991305,0.001250469,0.0005053157,0.000009695535],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2309632,0.001037375,0.7591665,0.000645633,0.0001701611,0.0001206003,0.0003738024,0.00216998,0.005352807],"genre_scores_gemma":[0.8905222,0.00035499,0.1044635,0.0002778611,0.00008349325,0.00007263877,0.0005259402,0.00007108709,0.003628444],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002286172,"threshold_uncertainty_score":0.004545748,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02763102561834377,"score_gpt":0.2710316218780534,"score_spread":0.2434005962597096,"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."}}