{"id":"W2357807430","doi":"","title":"A Comparative Study of MOS and PC Methods for Quality Evaluation of Text-to-Speech System in Mandarin","year":2006,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Speech Recognition and Synthesis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mandarin Chinese; Computer science; Active listening; Impression; Prosody; Speech recognition; Test (biology); Word (group theory); Quality (philosophy); Mean opinion score; Natural language processing; Psychology; Linguistics; Communication","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001538469,0.0001072603,0.0003420965,0.0002357402,0.00006314475,0.00003934265,0.0003323126,0.00003972911,0.000002014021],"category_scores_gemma":[0.000003244332,0.0001065439,0.00004274877,0.0005235036,0.00002704764,0.00008497549,0.0001151284,0.00004357793,0.000003111197],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006650016,"about_ca_system_score_gemma":0.0000470948,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002596063,"about_ca_topic_score_gemma":0.0001774929,"domain_scores_codex":[0.9983647,0.0003759218,0.000566137,0.000372305,0.0002026753,0.0001182682],"domain_scores_gemma":[0.9985902,0.0003799656,0.0002033163,0.0003331197,0.0004578175,0.00003556405],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001491313,0.001039715,0.001315834,0.0001045054,0.00003238861,1.133092e-7,0.00252945,0.0002624633,0.02156874,0.01135132,0.0001182055,0.9616624],"study_design_scores_gemma":[0.007109684,0.0005007697,0.2578013,0.0001703038,0.0001839117,0.00002629825,0.003866157,0.4235874,0.2828987,0.01314165,0.009914016,0.0007999395],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2346863,0.00004277989,0.7621596,0.00004103305,0.000008105268,0.002613287,0.00001173967,0.00002893639,0.0004081175],"genre_scores_gemma":[0.4671705,2.702654e-7,0.5318702,0.00001088073,0.00001145172,0.0009232647,0.000003503946,0.000003025039,0.00000688186],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9608624,"threshold_uncertainty_score":0.4344735,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08825679431518552,"score_gpt":0.4269068721197545,"score_spread":0.338650077804569,"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."}}