{"id":"W2889354736","doi":"10.1121/1.5051321","title":"Hyper-articulation in Lombard speech: An active communicative strategy to enhance visible speech cues?","year":2018,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Multisensory perception and integration","field":"Psychology","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Intelligibility (philosophy); QUIET; Modality (human–computer interaction); Articulation (sociology); Speech production; Speech recognition; Adaptation (eye); Reading aloud; Active listening; Computer science; Psychology; Reading (process); Linguistics; Communication; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.000564343,0.0005015485,0.0003002125,0.000288288,0.0004114504,0.0007872386,0.0002291101,0.0005061723,0.00109083],"category_scores_gemma":[0.00243516,0.0002213925,0.0001929633,0.00008078316,0.0007754483,0.0003835738,0.0006679957,0.0003233052,0.0002592349],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001998648,"about_ca_system_score_gemma":0.0002855171,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00254888,"about_ca_topic_score_gemma":0.003403767,"domain_scores_codex":[0.9996377,0.0001209186,0.0000125385,0.00008012651,0.0000875457,0.00006107888],"domain_scores_gemma":[0.999385,0.0002789639,0.0001245574,0.0000682351,0.0000703675,0.00007281102],"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":[0.0006337014,0.00005482582,0.01250135,0.0001352134,0.00002662118,0.0005568633,0.007218136,0.00009332038,0.9514575,0.000368424,0.00005730778,0.0268967],"study_design_scores_gemma":[0.00009981018,0.002687193,0.6795166,0.0001384976,0.0004301415,0.003868347,0.01679548,0.003082753,0.2845486,0.001123318,0.007588843,0.0001204209],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954157,0.0003013866,0.002242462,0.00005326312,0.000008430143,0.00001237526,0.000006269758,0.00002822889,0.001931867],"genre_scores_gemma":[0.9970098,0.0001276118,0.002056133,0.00003078922,0.000007745329,0.000007872202,0.00001084688,0.00001040325,0.0007387732],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00254888,"threshold_uncertainty_score":0.005068064,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05065071484316443,"score_gpt":0.3957263472387725,"score_spread":0.3450756323956081,"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."}}