{"id":"W4307680525","doi":"10.1162/tacl_a_00545","title":"Generative Spoken Dialogue Language Modeling","year":2023,"lang":"en","type":"article","venue":"Transactions of the Association for Computational Linguistics","topic":"Speech Recognition and Synthesis","field":"Computer Science","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Centre National de la Recherche Scientifique; Agence Nationale de la Recherche; École des Hautes Etudes en Sciences Sociales; Canadian Institute for Advanced Research","keywords":"Paralanguage; Computer science; Transformer; Spoken language; Generative grammar; Speech recognition; Natural language processing; Laughter; Language model; Artificial intelligence; Communication; Psychology","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":[0.0004964013,0.0007142774,0.0005202665,0.0004556214,0.0002579058,0.0008967351,0.001585908,0.001001605,0.006105737],"category_scores_gemma":[0.00187603,0.0004477058,0.001089799,0.0002956364,0.0005971885,0.0007330337,0.001227129,0.001312481,0.001485628],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006583724,"about_ca_system_score_gemma":0.0005910396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003346221,"about_ca_topic_score_gemma":0.003912078,"domain_scores_codex":[0.9995884,0.0001656848,0.00001480852,0.0001215123,0.00007110782,0.00003851092],"domain_scores_gemma":[0.9994465,0.0003549307,0.00002593448,0.00006309454,0.00007718395,0.00003228414],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001182076,0.00006031333,0.0008217345,0.0001256185,0.00009771445,0.0002338466,0.0003604821,0.8972139,0.005610975,0.03670106,0.004247938,0.05440823],"study_design_scores_gemma":[0.000005398521,0.000006064155,0.00003698372,0.000003512245,0.000003794134,0.00001607884,0.00000701379,0.9925356,0.0004099288,0.006069771,0.0009023522,0.000003478873],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02300226,0.0004296591,0.9671104,0.000496818,0.0001210391,0.00006603313,0.0008372,0.002569695,0.00536694],"genre_scores_gemma":[0.8106447,0.0002849512,0.1717802,0.0003824884,0.0001365318,0.0002818432,0.00211138,0.0005517321,0.01382609],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006105737,"threshold_uncertainty_score":0.0204258,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03106876500409547,"score_gpt":0.2777580017736145,"score_spread":0.246689236769519,"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."}}