{"id":"W2990506421","doi":"","title":"Speech Perception and The Role of Semantic Richness in Processing","year":2019,"lang":"en","type":"article","venue":"Canadian acoustics","topic":"Speech Recognition and Synthesis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Concreteness; Lexical decision task; Speech perception; Psychology; Valence (chemistry); Semantic property; Perception; Semantic memory; Cognitive psychology; Semantic similarity; Computer science; Speech recognition; Natural language processing; Cognition","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0007000117,0.0003813277,0.0002992176,0.0009050278,0.0002519824,0.001848391,0.0001938883,0.0003483139,0.002686784],"category_scores_gemma":[0.005326955,0.0002957628,0.0003463789,0.0003009042,0.0008981212,0.001854367,0.00160847,0.0003736816,0.0003014228],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002466245,"about_ca_system_score_gemma":0.0001873573,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009510684,"about_ca_topic_score_gemma":0.001050515,"domain_scores_codex":[0.9994671,0.000135789,0.00004234629,0.0001514642,0.0001501116,0.00005323398],"domain_scores_gemma":[0.9979558,0.001148774,0.0003731729,0.0001686005,0.0001992865,0.0001543279],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.002773933,0.000199457,0.1008838,0.0009879379,0.0004002274,0.0008571726,0.01167688,0.003276119,0.7148104,0.005862819,0.0005646529,0.1577066],"study_design_scores_gemma":[0.00008137252,0.0009731443,0.9335753,0.0001258695,0.0002392828,0.001187864,0.00470673,0.007351033,0.03138383,0.01770504,0.002533796,0.0001369219],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9801345,0.000646885,0.009913191,0.0001032361,0.00002483657,0.00002298151,0.0001482709,0.0000516734,0.008954375],"genre_scores_gemma":[0.9966173,0.0001978778,0.002660518,0.00003214391,0.00001675,0.00001143555,0.00008702054,0.00002144931,0.0003555549],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002686784,"threshold_uncertainty_score":0.008988261,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005660513892169393,"score_gpt":0.1943939282262723,"score_spread":0.1887334143341029,"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."}}