{"id":"W2022504354","doi":"10.1007/s10772-013-9203-7","title":"A novel sub-band adaptive filtering for acoustic echo cancellation based on empirical mode decomposition algorithm","year":2013,"lang":"en","type":"article","venue":"International Journal of Speech Technology","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Hilbert–Huang transform; Algorithm; Microphone; Echo (communications protocol); Adaptive filter; Transfer function; SIGNAL (programming language); Mode (computer interface); Noise (video); Speech recognition; Filter (signal processing); Artificial intelligence; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001607772,0.0001359134,0.0001848199,0.0007032868,0.00007295926,0.0001487625,0.000839095,0.0001377407,0.00001307065],"category_scores_gemma":[0.0001058536,0.000123372,0.00009113991,0.0002404257,0.00004943876,0.0005171514,0.00005980972,0.0002625061,0.000009907029],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002755107,"about_ca_system_score_gemma":0.0001516236,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001180403,"about_ca_topic_score_gemma":0.000007051632,"domain_scores_codex":[0.9987633,0.00001136462,0.0003872877,0.00022224,0.0004050071,0.0002108211],"domain_scores_gemma":[0.9983399,0.0001361166,0.0003942501,0.0001461619,0.000922932,0.00006067063],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0000654914,0.0001471346,0.0001636273,0.000005954617,0.00006231922,0.00004357163,0.00005156305,0.01684603,0.3866087,0.0001388278,0.0005660632,0.5953008],"study_design_scores_gemma":[0.000829599,0.0003310569,0.0001607931,0.000110322,0.000006903643,0.000289596,0.0000188536,0.4941426,0.4959581,0.007905412,0.0001419032,0.0001048556],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0436263,0.00003741183,0.948161,0.007212384,0.000630215,0.0001503424,0.000009389947,0.00006966652,0.0001032801],"genre_scores_gemma":[0.5466498,0.00000561312,0.4527747,0.0003451043,0.0001923849,0.0000121359,0.000002231817,0.000007501819,0.00001052514],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5951959,"threshold_uncertainty_score":0.5030965,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01989133890375423,"score_gpt":0.3417703319344523,"score_spread":0.3218789930306981,"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."}}