{"id":"W4360592708","doi":"10.2139/ssrn.4396565","title":"User Speech Rates and Preferences for System Speech Rates","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Speech recognition; Psychology; Preference; Competence (human resources); Computer science; Speech processing; Social 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":[0.001257215,0.0002712648,0.000275048,0.0005592179,0.0001963962,0.0008436924,0.0001445046,0.0004626781,0.008616126],"category_scores_gemma":[0.01583515,0.0001747467,0.0004029419,0.0003003436,0.0001192834,0.0006376609,0.000293223,0.0004310778,0.001581149],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001076369,"about_ca_system_score_gemma":0.00009190368,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001071028,"about_ca_topic_score_gemma":0.001278116,"domain_scores_codex":[0.9993579,0.0002066462,0.00009576621,0.00007722312,0.0001644617,0.0000980984],"domain_scores_gemma":[0.9781638,0.01585897,0.00167753,0.0008474869,0.00217091,0.001281378],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01165886,0.00078341,0.8404022,0.0002958995,0.0004452142,0.0007658785,0.003175717,0.002084948,0.07735608,0.0003025677,0.001146243,0.0615829],"study_design_scores_gemma":[0.00005680775,0.002502884,0.9730863,0.0000220505,0.0002353231,0.00236491,0.001920273,0.006116359,0.01246979,0.0001474555,0.0009896839,0.00008811757],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977881,0.00006828309,0.0004504955,0.00002214262,0.000006541896,0.000008930846,0.0001735852,0.00003780636,0.001444134],"genre_scores_gemma":[0.9981007,0.00005445199,0.0003891449,0.00002336196,0.00001055302,0.000008353622,0.0002447842,0.00002949665,0.001139162],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008616126,"threshold_uncertainty_score":0.02882379,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01700257559290255,"score_gpt":0.2712893970671886,"score_spread":0.2542868214742861,"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."}}