{"id":"W34538624","doi":"10.1016/j.encep.2021.04.004","title":"Reconfiguration of speech recognizers through layered-grammar structure to provide ease of navigation and recognition accuracy in speech-web.","year":2001,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Computer science; Speech recognition; Natural language processing; Grammar; Artificial intelligence; Linguistics","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":[0.0009832578,0.0004444456,0.0002521877,0.0003322275,0.0001480688,0.000903777,0.0006179858,0.0005103861,0.005052617],"category_scores_gemma":[0.008981956,0.0002151777,0.0004108321,0.0001501445,0.0003116398,0.001481353,0.0005742972,0.0005208337,0.002030081],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003269522,"about_ca_system_score_gemma":0.0005646677,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003018727,"about_ca_topic_score_gemma":0.003828873,"domain_scores_codex":[0.9993941,0.0001930314,0.00006213715,0.0001721607,0.0000943421,0.00008418308],"domain_scores_gemma":[0.9964809,0.001674819,0.0002547613,0.0006957516,0.0006601878,0.0002333832],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001484226,0.0009426553,0.01993071,0.0002739325,0.00009889618,0.0005831687,0.001083085,0.008086946,0.6008772,0.001712052,0.002546556,0.3623805],"study_design_scores_gemma":[0.0003311938,0.003015425,0.09423061,0.0001223112,0.000522327,0.002610347,0.0008136672,0.2300728,0.6465086,0.006958723,0.01451738,0.0002966743],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8355784,0.0002834607,0.148073,0.0003647884,0.0001807241,0.0002906819,0.0004620792,0.01096277,0.003804026],"genre_scores_gemma":[0.9219872,0.00008738509,0.07454791,0.0001261368,0.00001902285,0.0001231143,0.000401916,0.0002735201,0.002433976],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005052617,"threshold_uncertainty_score":0.01690274,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02751426649569214,"score_gpt":0.2671539902130342,"score_spread":0.239639723717342,"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."}}