{"id":"W6939194750","doi":"10.60692/38hgp-2s302","title":"Synthetic Speech Dataset","year":2019,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Speech Recognition and Synthesis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Speech synthesis; Speech processing; Spoken language; Natural language; Speech corpus; Speech technology","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":[0.001322155,0.003058478,0.001644732,0.00164954,0.001059052,0.001333748,0.002841087,0.00284618,0.03578993],"category_scores_gemma":[0.003828477,0.000503107,0.001518468,0.00149563,0.0005344246,0.00106688,0.001719665,0.002259947,0.06053051],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000889234,"about_ca_system_score_gemma":0.001651212,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01396901,"about_ca_topic_score_gemma":0.02081316,"domain_scores_codex":[0.9985311,0.0004172575,0.0001440333,0.0003207792,0.0004220498,0.0001646717],"domain_scores_gemma":[0.9977863,0.0006265842,0.00009173715,0.0006043216,0.0006789023,0.0002121483],"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":[0.001358509,0.0009767936,0.002205077,0.00176096,0.0003233504,0.0005152372,0.0001417805,0.009898364,0.00907511,0.001572845,0.8990965,0.0730755],"study_design_scores_gemma":[0.001738488,0.001132692,0.01996883,0.0003930271,0.0003173002,0.001812922,0.0005764456,0.04561719,0.01956964,0.003340301,0.9051996,0.0003335279],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01675593,0.0009774595,0.006605426,0.0005470659,0.001063585,0.0005250137,0.9535561,0.008290272,0.01167925],"genre_scores_gemma":[0.006714537,0.0001479473,0.002809897,0.0001288135,0.00004241854,0.0003478418,0.9865054,0.0001508223,0.003152179],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03578993,"threshold_uncertainty_score":0.1197293,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03117079637534485,"score_gpt":0.2093747215776078,"score_spread":0.178203925202263,"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."}}