{"id":"W4210322737","doi":"10.3390/app12031269","title":"Comparing the Effectiveness of Speech and Physiological Features in Explaining Emotional Responses during Voice User Interface Interactions","year":2022,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal","funders":"","keywords":"Human–computer interaction; Computer science; User interface; Interface (matter); Facial expression; Interactivity; CLARITY; User experience design; Speech recognition; Multimedia; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001922165,0.0006283446,0.0003406574,0.0008940434,0.0001283914,0.0009330586,0.0002245266,0.0007391347,0.001306967],"category_scores_gemma":[0.01210622,0.0001618147,0.0003919254,0.0003651578,0.0003728095,0.0008653373,0.0004341222,0.0002841568,0.0003144778],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001035317,"about_ca_system_score_gemma":0.0001295781,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003575255,"about_ca_topic_score_gemma":0.0004902032,"domain_scores_codex":[0.9987791,0.0005954397,0.00008236506,0.0002432739,0.0002267113,0.00007312904],"domain_scores_gemma":[0.9908771,0.007889258,0.0003759397,0.0001986519,0.0005187231,0.000140388],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.004951379,0.0007233025,0.1780703,0.00167871,0.0005021241,0.0003625384,0.005261849,0.005290497,0.425954,0.0005837309,0.0004622798,0.3761593],"study_design_scores_gemma":[0.00009551334,0.004127584,0.8953179,0.0001318187,0.0005148788,0.0008366898,0.00236182,0.04249755,0.05230501,0.0007163777,0.0009685129,0.0001263909],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9714407,0.0004873559,0.02513719,0.00004878606,0.00003051024,0.0001292433,0.0001776673,0.0001388158,0.002409927],"genre_scores_gemma":[0.9896051,0.0002065313,0.009644154,0.00002415326,0.00002485128,0.00006936785,0.0001204486,0.0000204465,0.0002848791],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001922165,"threshold_uncertainty_score":0.01016545,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07239905910417828,"score_gpt":0.3599792975016866,"score_spread":0.2875802383975083,"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."}}