{"id":"W2003125202","doi":"10.1109/icassp.2013.6637721","title":"A study of the MVDR filter for acoustic echo suppression","year":2013,"lang":"en","type":"article","venue":"","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique; Université du Québec à Montréal","funders":"","keywords":"Loudspeaker; Inverse filter; Microphone; Echo (communications protocol); Acoustics; Short-time Fourier transform; Computer science; SIGNAL (programming language); Filter (signal processing); Speech recognition; Fourier transform; Mathematics; Inverse; Physics; Fourier analysis; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009138911,0.0004960239,0.0005135199,0.0004175762,0.0002256477,0.0005763634,0.0005676795,0.0009649001,0.002788088],"category_scores_gemma":[0.003001665,0.0002597708,0.000499407,0.0004995041,0.0004489896,0.001066818,0.0003066907,0.0007472122,0.001137654],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003038369,"about_ca_system_score_gemma":0.0003215441,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000857111,"about_ca_topic_score_gemma":0.0006116253,"domain_scores_codex":[0.9992756,0.0001924674,0.00003138565,0.0001384492,0.0003288237,0.00003335402],"domain_scores_gemma":[0.9987338,0.0007792709,0.00005737246,0.0000875328,0.0003141727,0.00002784742],"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":[0.0003449092,0.0001152509,0.0008076995,0.0005847664,0.0001441349,0.0004113263,0.0003626277,0.1146403,0.220732,0.1339836,0.002398416,0.5254749],"study_design_scores_gemma":[0.00003086917,0.0003463085,0.0005564432,0.00007260738,0.00005350792,0.0007879078,0.00005667993,0.9013569,0.05538555,0.00854618,0.03275826,0.00004884238],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004247215,0.001421494,0.9917788,0.00008579691,0.00005130139,0.00001164195,0.00000747278,0.00008546421,0.002310912],"genre_scores_gemma":[0.2094836,0.005555818,0.7720162,0.0002802128,0.0004147455,0.00007446743,0.0001116067,0.0001718504,0.01189153],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002788088,"threshold_uncertainty_score":0.009327114,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02227971850545714,"score_gpt":0.2601872017903482,"score_spread":0.237907483284891,"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."}}