{"id":"W3007620998","doi":"10.1109/cogmi48466.2019.00012","title":"Self-Adaptive Tuning for Speech Enhancement Algorithm Based on Evolutionary Approach","year":2019,"lang":"en","type":"article","venue":"","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Moncton","funders":"","keywords":"Speech enhancement; Computer science; Intelligibility (philosophy); Evolutionary algorithm; Noise reduction; Algorithm; Speech recognition; Genetic algorithm; Artificial intelligence; Machine learning","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":[0.0003869873,0.000316079,0.0003033841,0.0004167302,0.0002394253,0.0003631527,0.0004875968,0.0004936495,0.0008056325],"category_scores_gemma":[0.0008070386,0.0001701743,0.0003209671,0.0001930224,0.000253672,0.0003670029,0.0002643626,0.0003612739,0.0001846979],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001968831,"about_ca_system_score_gemma":0.0002064959,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005681926,"about_ca_topic_score_gemma":0.0005161601,"domain_scores_codex":[0.9998136,0.00004113393,0.00001027173,0.00003869943,0.00007965979,0.00001668709],"domain_scores_gemma":[0.9997786,0.00009963736,0.00002736753,0.00002019834,0.00006567244,0.000008536675],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001059268,0.0001507958,0.00187139,0.0001302549,0.0001076316,0.0001837103,0.0002785804,0.4421779,0.1647067,0.01446372,0.0007460413,0.3750773],"study_design_scores_gemma":[0.00001110592,0.00008313071,0.0006042887,0.000009028371,0.00001807645,0.0001200256,0.00001538189,0.9848022,0.01118887,0.001191095,0.001944085,0.00001276362],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0328848,0.0002226441,0.9638748,0.00004510177,0.00002620811,0.00003652511,0.00000434486,0.000254209,0.002651404],"genre_scores_gemma":[0.5942246,0.0002548576,0.4015557,0.00007550369,0.00003026169,0.0001156436,0.00002861804,0.00006920433,0.003645755],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0008056325,"threshold_uncertainty_score":0.002695143,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01399248333215747,"score_gpt":0.231321284631762,"score_spread":0.2173288012996045,"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."}}