{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001574414,0.001139536,0.001264344,0.0008243113,0.001226562,0.003766528,0.00166291,0.001523629,0.06856751],"category_scores_gemma":[0.003628344,0.0005884484,0.0006537255,0.0006754266,0.0006981129,0.00225682,0.002477551,0.001146278,0.04946527],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006529307,"about_ca_system_score_gemma":0.001239779,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002165683,"about_ca_topic_score_gemma":0.002069309,"domain_scores_codex":[0.9982193,0.0004515762,0.0001383349,0.0003991561,0.0006753679,0.0001161323],"domain_scores_gemma":[0.998555,0.0004153232,0.00003106187,0.0003984871,0.0005121323,0.00008803732],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003717031,0.0001667137,0.000404356,0.0005971687,0.00007239686,0.0002023162,0.0006100687,0.00286122,0.03669309,0.03398991,0.2098604,0.7141708],"study_design_scores_gemma":[0.0001560894,0.000241196,0.001029353,0.0001886707,0.0001039689,0.000480662,0.0004811155,0.04121435,0.05206241,0.04012631,0.8638299,0.00008600698],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.01028491,0.005582465,0.7348098,0.001866624,0.003345977,0.0008280085,0.007713911,0.06839556,0.1671728],"genre_scores_gemma":[0.1953962,0.003101719,0.3547193,0.001476016,0.0009946214,0.00121585,0.03231666,0.006609962,0.4041695],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.06856751,"threshold_uncertainty_score":0.2293812,"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."}}