{"id":"W1935171541","doi":"10.1109/icassp.1997.596083","title":"Accurate keyword spotting using strictly lexical fillers","year":2002,"lang":"en","type":"article","venue":"","topic":"Text and Document Classification Technologies","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Keyword spotting; Computer science; Vocabulary; Set (abstract data type); Task (project management); Range (aeronautics); Directory; Natural language processing; Speech recognition; Artificial intelligence; Spotting; 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":[0.001108706,0.0008793117,0.001278122,0.0007282711,0.0003486152,0.001195406,0.001553042,0.001003097,0.005392503],"category_scores_gemma":[0.00523484,0.0005472028,0.0005270178,0.0005206279,0.0006531482,0.003155255,0.001182461,0.0006169492,0.004802076],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002600265,"about_ca_system_score_gemma":0.0005166395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005856733,"about_ca_topic_score_gemma":0.0008118656,"domain_scores_codex":[0.9989802,0.0001899419,0.0001744357,0.0002789844,0.0002776202,0.00009872784],"domain_scores_gemma":[0.9968255,0.001491894,0.0002380813,0.0007637103,0.0005188477,0.0001620518],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001951257,0.0001880733,0.001079941,0.0004968264,0.00005336082,0.0005126648,0.0003944136,0.009088666,0.4867247,0.006077172,0.002802048,0.4906308],"study_design_scores_gemma":[0.0001580146,0.001172063,0.001965046,0.00004678717,0.0001037928,0.001500697,0.0002835972,0.2667429,0.702206,0.008002078,0.01767638,0.0001424916],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07832672,0.0004182593,0.9072838,0.0001025015,0.0001267912,0.0001754518,0.0001799894,0.01060683,0.002779764],"genre_scores_gemma":[0.3532027,0.0002548025,0.6387876,0.0001898185,0.000141995,0.0003245915,0.0006308393,0.0007461526,0.005721568],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005392503,"threshold_uncertainty_score":0.0180397,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09808095789106017,"score_gpt":0.2754248937137858,"score_spread":0.1773439358227256,"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."}}