{"id":"W2161073483","doi":"10.1109/aspaa.1995.482974","title":"Exponentially decaying time-recursive blind deconvolution algorithm for speech dereverberation","year":2002,"lang":"en","type":"article","venue":"","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Blind deconvolution; Deconvolution; Algorithm; Recursion (computer science); Computer science; Impulse response; Adaptive filter; Finite impulse response; Computational complexity theory; Infinite impulse response; Adaptive algorithm; Impulse (physics); Signal processing; Speech recognition; Mathematics; Digital filter; Digital signal processing; Telecommunications","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":[0.0007078082,0.0005855525,0.0005192383,0.0003587248,0.000370824,0.0004882921,0.0009535,0.0008595613,0.002272627],"category_scores_gemma":[0.001738196,0.000244285,0.0003889908,0.000443539,0.0004377839,0.0007749219,0.0006927262,0.0009661829,0.001248865],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000415892,"about_ca_system_score_gemma":0.001056048,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001680928,"about_ca_topic_score_gemma":0.002735371,"domain_scores_codex":[0.9996527,0.00007467812,0.00001958495,0.00005458579,0.000164585,0.00003385781],"domain_scores_gemma":[0.9993879,0.0001927997,0.00004027738,0.0001070676,0.0002530679,0.00001891569],"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":[0.0002400304,0.00007711392,0.0003801589,0.0001095581,0.00004428913,0.00009558528,0.0001222156,0.1377736,0.07590599,0.04919031,0.003631929,0.7324293],"study_design_scores_gemma":[0.00002482668,0.00005875642,0.0002483635,0.000007918414,0.00001615573,0.0001297974,0.00000752527,0.9582248,0.02644824,0.007151294,0.007656953,0.00002540646],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002310959,0.0001199388,0.9966879,0.00003209916,0.00001942933,0.00001056531,0.00001240388,0.0003546588,0.0004519921],"genre_scores_gemma":[0.06054302,0.0003085879,0.9351094,0.00006328544,0.00003668357,0.00007234279,0.000100932,0.0001009133,0.003664896],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002272627,"threshold_uncertainty_score":0.007602751,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02473939933660236,"score_gpt":0.2460645035018116,"score_spread":0.2213251041652093,"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."}}