{"id":"W2986999147","doi":"10.1121/1.5137148","title":"Rating speech intelligibility using raw-audio as the input to a deep neural-network","year":2019,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Voice and Speech Disorders","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Intelligibility (philosophy); Computer science; Speech recognition; Active listening; Convolutional neural network; Artificial neural network; Correlation; Artificial intelligence; Mathematics; Psychology","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":[0.001869625,0.001157852,0.0004793767,0.0006645559,0.000159367,0.0008308585,0.0003603673,0.0006525733,0.003086649],"category_scores_gemma":[0.009597397,0.0001829391,0.0004753787,0.0003249327,0.0002952491,0.0006915695,0.0008496888,0.0005540882,0.001135555],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002502299,"about_ca_system_score_gemma":0.0003060694,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001576188,"about_ca_topic_score_gemma":0.002797159,"domain_scores_codex":[0.9990971,0.0002942716,0.0001135524,0.0001595767,0.0002762818,0.00005929861],"domain_scores_gemma":[0.9970493,0.001664229,0.0001818199,0.0002388933,0.0007374291,0.0001283776],"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":[0.004915608,0.001229502,0.1282101,0.001079415,0.0009146378,0.001058457,0.00100162,0.1865726,0.1838454,0.0008588536,0.004277176,0.4860365],"study_design_scores_gemma":[0.0001247636,0.002813083,0.1164379,0.0001082003,0.0002125363,0.0009133827,0.000484975,0.7775232,0.09790883,0.001427045,0.001900087,0.0001459162],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8797556,0.0004236621,0.1124688,0.0001754209,0.0001348032,0.0002741129,0.002063405,0.00143485,0.00326946],"genre_scores_gemma":[0.956899,0.0001547534,0.03977499,0.00006053519,0.00001921134,0.0001440176,0.001326102,0.00009318547,0.001528252],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003086649,"threshold_uncertainty_score":0.01032591,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01741326326263275,"score_gpt":0.2986848353411615,"score_spread":0.2812715720785287,"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."}}