{"id":"W4211147687","doi":"10.2200/s00204ed1v01y200910hlt005","title":"Spoken Dialogue Systems","year":2009,"lang":"en","type":"article","venue":"Synthesis lectures on human language technologies","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":58,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Spoken language; Computer science; Multimodality; Adaptation (eye); Communicative competence; Competence (human resources); Human–computer interaction; Natural language processing; Artificial intelligence; Linguistics; Psychology; World Wide Web","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003134755,0.000334458,0.0004241003,0.000517842,0.0002665263,0.0003572048,0.002124099,0.0003175897,0.0000116259],"category_scores_gemma":[0.000762635,0.0002556723,0.0001364351,0.0004706676,0.0001066522,0.000200734,0.0001439657,0.0003008877,0.0001880343],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009375965,"about_ca_system_score_gemma":0.00002799979,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001253702,"about_ca_topic_score_gemma":0.00003350016,"domain_scores_codex":[0.9979683,0.0001089577,0.000317766,0.0006360403,0.0003974207,0.0005714885],"domain_scores_gemma":[0.9978701,0.0002814985,0.0001532342,0.001596169,0.00004048508,0.00005850779],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004533198,0.0003487605,0.0002425491,0.00008449372,0.0001165601,0.0008020937,0.002400376,0.0002728072,0.1007245,0.4783296,0.01830878,0.3983241],"study_design_scores_gemma":[0.0009159831,0.001662683,0.006775625,0.000574122,0.0000561811,0.0002418254,0.003660189,0.0007664098,0.9121972,0.06258272,0.008118405,0.002448694],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7331932,0.0224579,0.05864312,0.01047039,0.003139491,0.003272738,0.00008265128,0.05115875,0.1175818],"genre_scores_gemma":[0.9979921,0.00001678352,0.001361889,0.0002296387,0.0001340532,0.00007418898,0.000004639482,0.00001628679,0.0001704103],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8114727,"threshold_uncertainty_score":0.9999896,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01943691375922096,"score_gpt":0.2708791217803281,"score_spread":0.2514422080211071,"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."}}