{"id":"W1968815172","doi":"10.1121/1.3508579","title":"Improving the speech intelligibility of forensic audio recordings through adaptive filtering with non-synchronous interference signals.","year":2010,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Microstructural Sciences; National Research Council Canada; Royal Canadian Mounted Police","funders":"","keywords":"Intelligibility (philosophy); Computer science; Speech recognition; Adaptive filter; Active listening; Communication","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":[0.001053041,0.0005435018,0.0002756019,0.0007213518,0.0001711921,0.0004636147,0.0005152347,0.0006090924,0.001381193],"category_scores_gemma":[0.00405944,0.0001552801,0.0002998853,0.000336508,0.0004003496,0.0007063847,0.0003193129,0.000329089,0.0005975956],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001054469,"about_ca_system_score_gemma":0.0001869985,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000208217,"about_ca_topic_score_gemma":0.0005186964,"domain_scores_codex":[0.9995754,0.0001287489,0.00003583249,0.00007167171,0.0001658582,0.00002245682],"domain_scores_gemma":[0.9984193,0.001005646,0.0001575262,0.0001391511,0.0002339784,0.00004429833],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004927046,0.0001038627,0.000889676,0.0003478323,0.00003881724,0.0001892813,0.0001605042,0.0008160265,0.7812466,0.0002951373,0.0001853452,0.2152342],"study_design_scores_gemma":[0.00006197928,0.002001742,0.01272332,0.00007039743,0.0002160432,0.002231963,0.0001401264,0.01489308,0.9617924,0.0003680119,0.005456043,0.00004483819],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4706971,0.003234872,0.5216168,0.0001791626,0.0001468762,0.0001858881,0.0001038087,0.0007568738,0.003078548],"genre_scores_gemma":[0.6417755,0.002669103,0.3523802,0.0001320547,0.0001048046,0.00009192981,0.0002585191,0.0001044267,0.002483423],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001381193,"threshold_uncertainty_score":0.005569041,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01341300088112723,"score_gpt":0.2410979686536659,"score_spread":0.2276849677725387,"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."}}