{"id":"W1898340511","doi":"10.1109/icassp.1976.1169963","title":"Computer synthesis of Mandarin","year":2005,"lang":"en","type":"article","venue":"","topic":"Speech Recognition and Synthesis","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Mandarin Chinese; Speech recognition; Intelligibility (philosophy); Computer science; Syllable; String (physics); Speech synthesis; Mathematics; Linguistics","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":[0.0002962775,0.0003934891,0.0003367689,0.0004734787,0.0002533776,0.0004195649,0.0002683526,0.0003312837,0.009709453],"category_scores_gemma":[0.000775538,0.0001320682,0.000222577,0.0003472243,0.0001503776,0.0001977167,0.000252731,0.0002014956,0.001448139],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002230328,"about_ca_system_score_gemma":0.0002865386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001015433,"about_ca_topic_score_gemma":0.001278479,"domain_scores_codex":[0.9998362,0.0000280198,0.00001659596,0.00005253813,0.00004716041,0.00001940246],"domain_scores_gemma":[0.9997931,0.00009177748,0.00000791337,0.00002437152,0.00007258355,0.00001027719],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0009905584,0.000130825,0.0004736044,0.0006730736,0.00005842408,0.0006192207,0.0005914335,0.02341848,0.6981927,0.01449459,0.003570024,0.2567872],"study_design_scores_gemma":[0.0003937011,0.002421353,0.006327342,0.00008089337,0.0001818579,0.00124255,0.0002845535,0.2055017,0.6452292,0.00537452,0.1328559,0.0001064695],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4262278,0.001266965,0.4982823,0.000283896,0.000525418,0.0006289732,0.00209246,0.007558573,0.06313369],"genre_scores_gemma":[0.7133208,0.0004438985,0.2661799,0.0001156351,0.00007742852,0.0004799483,0.002780247,0.0004690215,0.01613319],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009709453,"threshold_uncertainty_score":0.03248131,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01552820141597256,"score_gpt":0.228906391700665,"score_spread":0.2133781902846925,"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."}}