{"id":"W4393475061","doi":"10.5281/zenodo.1478765","title":"A Canadian French Emotional Speech Dataset","year":2018,"lang":"en","type":"dataset","venue":"Figshare","topic":"Speech Recognition and Synthesis","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Speech recognition; Computer science; Psychology; Natural language processing","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":[0.001286269,0.004358134,0.001491917,0.004397152,0.00327464,0.001948535,0.003521181,0.003052324,0.03722359],"category_scores_gemma":[0.004376249,0.0004565637,0.001519394,0.003545022,0.0008390025,0.001035606,0.001962733,0.002079912,0.04079878],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005720241,"about_ca_system_score_gemma":0.00824149,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5791948,"about_ca_topic_score_gemma":0.7122421,"domain_scores_codex":[0.9978783,0.0003068351,0.0001232782,0.000487729,0.0007874659,0.0004164632],"domain_scores_gemma":[0.9973979,0.0003403477,0.00006153456,0.000352445,0.00160836,0.0002393669],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003086209,0.0001326142,0.001584543,0.0005808881,0.00008548967,0.0003103534,0.0001445503,0.0007659098,0.001777512,0.0006933591,0.9623495,0.03126669],"study_design_scores_gemma":[0.0002564007,0.0001263168,0.03277449,0.0004206813,0.0001437348,0.001032603,0.0007404083,0.005657224,0.003840878,0.0006777798,0.954133,0.0001963849],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.008278704,0.001152914,0.001402305,0.0004423549,0.0003449842,0.0003580103,0.9762964,0.002710885,0.009013459],"genre_scores_gemma":[0.005315162,0.0002194945,0.001700566,0.0001220853,0.00004319931,0.0003310729,0.9868647,0.0001428745,0.005260874],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4208052,"threshold_uncertainty_score":0.8465669,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04705013687903825,"score_gpt":0.2665401403992551,"score_spread":0.2194900035202168,"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."}}