{"id":"W3172764674","doi":"10.1002/cav.2016","title":"ExpressGesture: Expressive gesture generation from speech through database matching","year":2021,"lang":"en","type":"article","venue":"Computer Animation and Virtual Worlds","topic":"Hand Gesture Recognition Systems","field":"Computer Science","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"ADAPT - Centre for Digital Content Technology; University of California, Davis; University of Toronto; Science Foundation Ireland","keywords":"Gesture; Computer science; Speech recognition; Gesture recognition; Motion capture; Artificial intelligence; Motion (physics)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.001042583,0.001097799,0.001064146,0.001230249,0.0003370932,0.001013193,0.00183156,0.000869618,0.009712484],"category_scores_gemma":[0.002271627,0.0004748896,0.0008074497,0.0006860989,0.000529147,0.001498039,0.001560597,0.0006252045,0.003234255],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004150334,"about_ca_system_score_gemma":0.0003964089,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002135621,"about_ca_topic_score_gemma":0.002623203,"domain_scores_codex":[0.9989181,0.0002341107,0.00006657719,0.0004456261,0.0002684074,0.00006721105],"domain_scores_gemma":[0.9991272,0.0004091021,0.00004995213,0.0002575786,0.0001050685,0.00005120855],"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":[0.0007197289,0.0002280021,0.001777178,0.0002776186,0.0001203922,0.0003902354,0.0002866031,0.03079193,0.09150488,0.003197599,0.009989921,0.8607159],"study_design_scores_gemma":[0.0001039385,0.0002099087,0.002235539,0.00002611856,0.00004622547,0.0006246113,0.0002056717,0.8839506,0.09558575,0.005302754,0.01164665,0.00006229898],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05470331,0.0003543593,0.906983,0.0001192732,0.00008663962,0.0002230291,0.001169682,0.03320438,0.003156268],"genre_scores_gemma":[0.4292409,0.0002516328,0.5528675,0.0002449978,0.00005580779,0.0003777249,0.005037901,0.002035182,0.009888285],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009712484,"threshold_uncertainty_score":0.03249151,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03317050590792655,"score_gpt":0.2683416722137332,"score_spread":0.2351711663058066,"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."}}