{"id":"W2620616604","doi":"","title":"Predicting the quality of processed speech by combining modulation-based features and model trees.","year":2016,"lang":"en","type":"article","venue":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","topic":"Speech Recognition and Synthesis","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Institut National de la Recherche Scientifique","funders":"","keywords":"Computer science; Quality (philosophy); Speech recognition; Modulation (music); Artificial intelligence; Pattern recognition (psychology); Acoustics","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":[0.0006073345,0.0006160561,0.0005360493,0.001161564,0.000186988,0.0007144102,0.0003291107,0.0008449169,0.001728428],"category_scores_gemma":[0.003602423,0.000317675,0.0005792825,0.0006232751,0.0001840329,0.001010607,0.0004433482,0.0007620931,0.00119965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002469417,"about_ca_system_score_gemma":0.0003031895,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003389814,"about_ca_topic_score_gemma":0.005197717,"domain_scores_codex":[0.9997726,0.00006486203,0.00001226248,0.00005174779,0.00006363637,0.00003491111],"domain_scores_gemma":[0.9988784,0.000751294,0.00008728571,0.00006217253,0.0001768339,0.00004397179],"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":[0.001673113,0.0004140601,0.02497564,0.0001877349,0.0002869703,0.0002833831,0.0001239069,0.3070995,0.1515188,0.001712202,0.004667038,0.5070576],"study_design_scores_gemma":[0.00001407323,0.00008397392,0.006895192,0.00000829753,0.00003957084,0.00005140508,0.00001215616,0.984934,0.006922916,0.0007920421,0.0002357575,0.00001058213],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4106472,0.001396978,0.5806172,0.00039371,0.0001853532,0.00008333501,0.001225083,0.0021974,0.003253775],"genre_scores_gemma":[0.9299027,0.0003233447,0.06706256,0.00004433168,0.00005337273,0.00003189956,0.001242412,0.0001448405,0.001194573],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003389814,"threshold_uncertainty_score":0.006740153,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03210785264559545,"score_gpt":0.2759148809231232,"score_spread":0.2438070282775278,"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."}}