{"id":"W6928990647","doi":"10.48448/208h-5v40","title":"Learning Robust Latent Representations for Controllable Speech Synthesis","year":2021,"lang":"en","type":"other","venue":"Underline Science Inc.","topic":"Cystic Fibrosis Research Advances","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Transformer; Latent variable; Mutual information; Encoder; Probabilistic latent semantic analysis; Encoding (memory); ENCODE; Feature learning; Speech synthesis","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007377535,0.0002281088,0.0005370583,0.0006290051,0.0002810195,0.000148106,0.000326195,0.0001313391,0.003703068],"category_scores_gemma":[0.006945269,0.0001957275,0.0001194061,0.0009170728,0.0007119194,0.0000843834,0.0001502206,0.0003333467,0.00006926752],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002256525,"about_ca_system_score_gemma":0.001239507,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002930128,"about_ca_topic_score_gemma":0.0002822368,"domain_scores_codex":[0.9972144,0.00004959541,0.000305267,0.0007857303,0.001010218,0.0006347485],"domain_scores_gemma":[0.9978138,0.0006667399,0.0001852376,0.000559313,0.0004838762,0.0002909997],"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":[0.0005096858,0.001076589,0.004348632,0.002727098,0.0007769722,0.0004541446,0.000226061,0.007526798,0.1432014,0.002769719,0.6344992,0.2018837],"study_design_scores_gemma":[0.002768752,0.0006823644,0.0006580966,0.002514784,0.0003524499,0.000157148,0.001028234,0.06677391,0.01150639,0.000305589,0.912549,0.0007033517],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.000700545,0.008093486,0.04118655,0.00824755,0.001551857,0.005762954,0.0002860532,0.0008610321,0.93331],"genre_scores_gemma":[0.004250378,0.0003982897,0.1815958,0.0001296095,0.0006172941,0.0002331512,0.0001907203,0.0002498688,0.8123348],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.2780497,"threshold_uncertainty_score":0.9972077,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04590396584984031,"score_gpt":0.3580492221138035,"score_spread":0.3121452562639632,"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."}}