{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001309043,0.00005536979,0.000104227,0.00007521447,0.00002513257,0.00003456311,0.0003549838,0.00002615635,0.0006127139],"category_scores_gemma":[0.00001803702,0.00004498026,0.00005696444,0.0001174773,0.0000208417,0.0001862771,0.00008139327,0.00002662556,0.0003521575],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009520126,"about_ca_system_score_gemma":0.00001432331,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008417845,"about_ca_topic_score_gemma":0.000007781924,"domain_scores_codex":[0.9994504,0.00002449524,0.000144188,0.0001406082,0.0001381515,0.0001021604],"domain_scores_gemma":[0.9994904,0.0001411001,0.00003445009,0.0002483788,0.00004220772,0.00004350522],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[8.879975e-7,0.00003967807,0.00009058038,0.000002728323,0.000007004598,0.000001241618,0.00003028225,0.000004164112,0.0001588396,0.01773076,0.002618764,0.979315],"study_design_scores_gemma":[0.0003092956,0.00005450397,0.007498182,0.0000400223,0.00001115706,0.00004903879,0.000017631,0.214278,0.6893702,0.001619532,0.08641507,0.0003373296],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008766503,0.00001280281,0.881821,0.001911656,0.00009556305,0.00004707231,0.000001143856,0.0001465001,0.1071977],"genre_scores_gemma":[0.4134089,0.000004972225,0.5855314,0.0004942422,0.00005276004,0.000003635132,1.055501e-7,0.00000249763,0.0005014939],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9789777,"threshold_uncertainty_score":0.6708788,"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."}}