{"id":"W4375868876","doi":"10.1109/icassp49357.2023.10095598","title":"Towards Dialogue Modeling Beyond Text","year":2023,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Ontario; University of Toronto","funders":"","keywords":"Conversation; Computer science; Modalities; Component (thermodynamics); Active listening; Multimodality; Modality (human–computer interaction); Multimodal interaction; Natural language processing; Human–computer interaction; Speech recognition; Artificial intelligence; Linguistics; World Wide Web; Communication; Psychology","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003155652,0.00008929881,0.0001158734,0.0001348658,0.00007951446,0.0001388708,0.0006088205,0.00005167547,0.00002060876],"category_scores_gemma":[0.00004846248,0.00007316613,0.00005864917,0.0006748498,0.00001055087,0.0002799474,0.000247928,0.00005731198,0.002736286],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001792654,"about_ca_system_score_gemma":0.00007080258,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003821822,"about_ca_topic_score_gemma":0.00004890982,"domain_scores_codex":[0.9989805,0.00002751548,0.0001609124,0.0002810867,0.0002394262,0.0003105472],"domain_scores_gemma":[0.9993609,0.00003378116,0.00001940411,0.0004323337,0.0000440363,0.0001095005],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000009409806,0.00006237645,0.0006122728,0.00004177858,0.00004342516,0.000157695,0.002714468,0.01455864,0.002898746,0.7029499,0.0897447,0.1862066],"study_design_scores_gemma":[0.0001981564,0.00002914019,0.0002529457,0.000005721921,0.000001362103,0.000008877453,0.00006189947,0.9567666,0.0009455019,0.03882186,0.002736979,0.0001709701],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01803774,0.00005177409,0.8359611,0.001466787,0.001510127,0.0001273126,0.000002805548,0.001303148,0.1415392],"genre_scores_gemma":[0.9874545,0.000009473051,0.01010715,0.0004185062,0.0002137549,0.00001531352,0.000009548152,0.000007888098,0.001763878],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9694167,"threshold_uncertainty_score":0.9980402,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03276172241210811,"score_gpt":0.255899805484269,"score_spread":0.2231380830721609,"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."}}