{"id":"W1511899752","doi":"10.5281/zenodo.38101","title":"Nonlinear Speech Processing With Oscillatory Neural Networks For Speaker Segregation","year":2002,"lang":"en","type":"article","venue":"","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Chicoutimi","funders":"","keywords":"Computer science; Speech recognition; Filter bank; Representation (politics); Artificial neural network; Nonlinear system; Context (archaeology); Speech processing; Masking (illustration); Artificial intelligence; Filter (signal processing); Computer vision","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001300666,0.0001474598,0.0001296424,0.00006257251,0.0002279275,0.0003646845,0.0003369109,0.00005602103,0.00002772472],"category_scores_gemma":[0.00001539663,0.0001084655,0.0000379512,0.000399902,0.00003831521,0.0009300333,0.0000510781,0.0001039934,0.000012473],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002594902,"about_ca_system_score_gemma":0.00002462773,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002442901,"about_ca_topic_score_gemma":0.00001156709,"domain_scores_codex":[0.9988801,0.00001155172,0.000166337,0.0003719505,0.0002206718,0.0003493688],"domain_scores_gemma":[0.9993953,0.00003278356,0.00009561256,0.0002385188,0.0001477212,0.00009011084],"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":[0.00001037584,0.00005767907,0.001020855,0.00004007302,0.000008066312,0.00001344387,0.0002093531,0.002684645,0.0003973366,0.0001721958,0.001556088,0.9938299],"study_design_scores_gemma":[0.0004020895,0.00009535567,0.0001028494,0.00002895136,0.000005313001,0.00005744143,0.00001685498,0.9832526,0.01355158,0.0001732166,0.002114757,0.0001989529],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03587251,0.0003736053,0.9582285,0.001058034,0.0001433618,0.0002219458,4.23053e-7,0.0003348796,0.003766742],"genre_scores_gemma":[0.4914199,0.000004375121,0.5060426,0.0010068,0.0002626702,0.00001076158,0.000002089598,0.00001696325,0.00123388],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9936309,"threshold_uncertainty_score":0.4423096,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01998849107640897,"score_gpt":0.2305301715518223,"score_spread":0.2105416804754133,"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."}}