{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00192212,0.0001865785,0.0002301026,0.0002024679,0.0004499231,0.000624615,0.0006930904,0.00007545359,0.000002897676],"category_scores_gemma":[0.00008183625,0.0001467648,0.00007558191,0.0005505108,0.0000375361,0.0006862087,0.0001189091,0.0006306335,0.00004562554],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002208119,"about_ca_system_score_gemma":0.001124237,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001489656,"about_ca_topic_score_gemma":0.0001198658,"domain_scores_codex":[0.9970675,0.00006078939,0.0002845545,0.0003554055,0.0002818415,0.001949971],"domain_scores_gemma":[0.9992242,0.0001510502,0.0001723067,0.0001908024,0.000149333,0.0001122924],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00008722715,0.00007005564,0.01729444,0.0003118594,0.000369453,0.00007632239,0.0007037855,0.00005197633,0.01448024,0.120063,0.002818729,0.8436729],"study_design_scores_gemma":[0.002727828,0.001302608,0.003859812,0.0004782231,0.00008082628,0.005041561,0.006050233,0.01019366,0.2474701,0.7161769,0.005494386,0.001123846],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8646237,0.004734457,0.1268582,0.001826449,0.0006277785,0.0003283338,0.00000315719,0.0004259875,0.0005719058],"genre_scores_gemma":[0.9849131,0.001641075,0.01050501,0.00007869107,0.0004248902,0.00001718184,0.000003101145,0.0000233124,0.002393599],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8425491,"threshold_uncertainty_score":0.6023177,"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."}}