{"id":"W6997174494","doi":"","title":"Utilization of Multiple Units in Human And Machine Recognition of Continuous Speech---- Perceptual Evidence And A Proposal For An Asr System","year":2022,"lang":"en","type":"article","venue":"Canadian acoustics","topic":"Speech Recognition and Synthesis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Perception; Pattern recognition (psychology); Human–machine system; Human–machine interface","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.002919164,0.0004616692,0.0006689551,0.0008270509,0.0005777224,0.002799419,0.001508578,0.001405551,0.004027681],"category_scores_gemma":[0.006711768,0.0006628399,0.0005804916,0.0007069016,0.002331137,0.005429582,0.001430354,0.001194815,0.0009255414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003838723,"about_ca_system_score_gemma":0.0004506954,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007836919,"about_ca_topic_score_gemma":0.0008061205,"domain_scores_codex":[0.9989152,0.0003504257,0.0001194829,0.0003263176,0.0002117046,0.00007688578],"domain_scores_gemma":[0.9955155,0.002366661,0.000253944,0.001067968,0.000638756,0.0001572196],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002426637,0.0002054051,0.006081905,0.0005430389,0.0001738199,0.0009209331,0.002331611,0.00528065,0.2579163,0.252134,0.001600819,0.4703849],"study_design_scores_gemma":[0.0003959291,0.002604146,0.03147158,0.0004286947,0.000628339,0.005424905,0.003147245,0.2874955,0.1980243,0.4446929,0.02529101,0.000395508],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3079244,0.004284234,0.6504594,0.003293616,0.0005842343,0.0001568053,0.0002363593,0.0008948444,0.03216605],"genre_scores_gemma":[0.8276561,0.0006128008,0.1666489,0.0002516693,0.0001910559,0.0001284525,0.00007213011,0.0001213309,0.004317585],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004027681,"threshold_uncertainty_score":0.0154382,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09954456807472184,"score_gpt":0.2733270052505045,"score_spread":0.1737824371757826,"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."}}