{"id":"W4382862298","doi":"10.3390/electronics12132887","title":"Review of Advances in Speech Processing with Focus on Artificial Neural Networks","year":2023,"lang":"en","type":"article","venue":"Electronics","topic":"Speech Recognition and Synthesis","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Focus (optics); Computer science; Speech processing; Artificial neural network; Hidden Markov model; Coding (social sciences); Artificial intelligence; Speech recognition","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003060319,0.00008529826,0.0001654059,0.000100056,0.00003561073,0.00002584122,0.0002546214,0.00002771636,0.000009264594],"category_scores_gemma":[0.00004499471,0.00006789035,0.00003148383,0.001186013,0.00001831851,0.0002068339,0.00002557899,0.0001555486,0.00001438805],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000329678,"about_ca_system_score_gemma":0.00007485423,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":7.909164e-7,"about_ca_topic_score_gemma":0.00008254356,"domain_scores_codex":[0.9990805,0.0000489016,0.0001891154,0.0002066085,0.0001872785,0.0002875942],"domain_scores_gemma":[0.9995945,0.00007235681,0.00008554167,0.0001727347,0.0000474571,0.00002739958],"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":[0.00000928576,0.00002165875,0.00002793711,0.0001345704,0.000001566621,0.00001096111,0.00001493406,0.0001768868,0.00002208644,0.001257534,0.0001132876,0.9982093],"study_design_scores_gemma":[0.0007270342,0.00146699,0.0006964136,0.01030073,0.00003046793,0.0001014982,0.00004918165,0.8720497,0.03733219,0.02332463,0.05301784,0.0009033373],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.04894064,0.7954342,0.1260452,0.01211511,0.0005208864,0.001466375,0.000003556799,0.001061165,0.01441287],"genre_scores_gemma":[0.7119158,0.2701083,0.0140586,0.00333807,0.0002552842,0.0001059118,0.0000132414,0.00005434936,0.000150457],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.9973059,"threshold_uncertainty_score":0.2768488,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0198451927513029,"score_gpt":0.2754517902035622,"score_spread":0.2556065974522593,"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."}}