{"id":"W3210917154","doi":"10.3390/s21217025","title":"A Hybrid Speech Enhancement Algorithm for Voice Assistance Application","year":2021,"lang":"en","type":"article","venue":"Sensors","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Speech recognition; Computer science; Voice activity detection; Speech enhancement; Audio mining; Speech coding; Intelligibility (philosophy); Speech processing; Acoustic model; Background noise; Linear predictive coding; Noise (video); Hidden Markov model; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001399404,0.00009465299,0.0001093705,0.00002864029,0.0001262514,0.0001422742,0.0002615815,0.00002374213,0.000007309273],"category_scores_gemma":[0.00003987641,0.00009791202,0.00005205841,0.0002142736,0.00001590089,0.0001625309,0.00006178388,0.00005778052,0.00008719488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004842972,"about_ca_system_score_gemma":0.00008332318,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003449741,"about_ca_topic_score_gemma":0.000003838321,"domain_scores_codex":[0.9989802,0.00001808908,0.0001515271,0.0004118218,0.0001952145,0.0002431951],"domain_scores_gemma":[0.9992294,0.00005147272,0.00007841573,0.0003747256,0.0002056309,0.00006039015],"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":[0.000001506347,0.00004043103,0.00001068599,0.0000176447,0.000008850097,0.00001973128,0.00005173501,0.00002260385,0.02442559,0.0003588309,0.001160128,0.9738823],"study_design_scores_gemma":[0.0002031603,0.00001775339,0.00006536033,0.00001628958,0.000004304895,0.00003274332,0.00001647003,0.065273,0.8671077,0.002877389,0.06425352,0.0001322771],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03478568,0.0002324762,0.9620175,0.001070928,0.0002142203,0.0001459516,0.000004933803,0.00009878511,0.001429543],"genre_scores_gemma":[0.04963233,0.00002071775,0.9468657,0.0006558915,0.0001771518,0.00004920346,0.00001288116,0.00001036877,0.002575773],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.97375,"threshold_uncertainty_score":0.3992736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01159835366218354,"score_gpt":0.2574067036717646,"score_spread":0.2458083500095811,"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."}}