{"id":"W1557290754","doi":"","title":"Coherent and incoherent interference reduction using a subband tradeoff beamformer","year":2011,"lang":"en","type":"article","venue":"European Signal Processing Conference","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":"Interference (communication); Computer science; Reduction (mathematics); Perspective (graphical); Distortion (music); Noise (video); Noise reduction; Beamforming; Speech recognition; Set (abstract data type); Acoustics; Signal-to-noise ratio (imaging); Algorithm; Mathematics; Artificial intelligence; Telecommunications; Physics; Bandwidth (computing); Image (mathematics)","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":[0.001275669,0.001005747,0.0007715704,0.0005401277,0.0002109383,0.0007060866,0.0006540035,0.001158862,0.00238254],"category_scores_gemma":[0.002575342,0.0005294156,0.0006879872,0.0006181417,0.000546384,0.001355147,0.001133759,0.0006609475,0.001371226],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002496178,"about_ca_system_score_gemma":0.000381379,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00018836,"about_ca_topic_score_gemma":0.0003866794,"domain_scores_codex":[0.9988991,0.0003582896,0.00007340126,0.0001962108,0.0004231067,0.00004996579],"domain_scores_gemma":[0.9991367,0.0003084892,0.00009097328,0.0001421824,0.0002805343,0.00004110369],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001215574,0.0001554707,0.001259557,0.0002379491,0.0002489728,0.0001555794,0.0003731516,0.1113741,0.4971144,0.02324808,0.001672948,0.3629442],"study_design_scores_gemma":[0.0002270288,0.001112196,0.00218738,0.00005313515,0.0002215794,0.001363131,0.0001368132,0.757637,0.2048236,0.01510431,0.01700738,0.000126548],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009790831,0.0001556466,0.9887767,0.00006793001,0.00002465159,0.00002027757,0.00001489402,0.0001518602,0.0009972546],"genre_scores_gemma":[0.1447172,0.0003831763,0.850494,0.0001629951,0.0000555826,0.0001331049,0.0001160058,0.0000957633,0.003842323],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00238254,"threshold_uncertainty_score":0.007970393,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08395056231313583,"score_gpt":0.2503585055145274,"score_spread":0.1664079432013916,"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."}}