{"id":"W2107019147","doi":"10.1109/icassp.2006.1660588","title":"The Effect of Memory Inclusion on Mutual Information Between Speech Frequency Bands","year":2006,"lang":"en","type":"article","venue":"","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Correlation; Disjoint sets; Entropy (arrow of time); Gaussian; Speech recognition; Cepstrum; Mutual information; Parametrization (atmospheric modeling); Bandwidth (computing); Computer science; Mathematics; Artificial intelligence; Physics; Telecommunications; Mathematical analysis","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":[0.002505165,0.0007005869,0.0007370724,0.0006349615,0.0005077738,0.001195977,0.0008514008,0.0008676623,0.001478419],"category_scores_gemma":[0.03017744,0.0004889211,0.0004029884,0.0006028779,0.001020283,0.003167752,0.002448868,0.000901891,0.0002452268],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004073859,"about_ca_system_score_gemma":0.000645409,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008509779,"about_ca_topic_score_gemma":0.001075904,"domain_scores_codex":[0.9985803,0.0004501059,0.0001034366,0.0002375577,0.0003990456,0.0002294896],"domain_scores_gemma":[0.9655349,0.02912734,0.001826991,0.002196505,0.0009246651,0.0003895161],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.006539659,0.0006164057,0.03665347,0.0007931425,0.0005575252,0.001774741,0.00100001,0.3655397,0.2400425,0.0132402,0.0006851801,0.3325574],"study_design_scores_gemma":[0.0000723034,0.002046237,0.03769745,0.0001155172,0.0005050554,0.001699184,0.000307271,0.6569452,0.2916057,0.007464289,0.001385318,0.0001563962],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8883397,0.001052661,0.1060101,0.0002628102,0.00004870782,0.00002143672,0.00008715563,0.0004638764,0.003713562],"genre_scores_gemma":[0.9938561,0.0001473352,0.00556165,0.00002815791,0.00001936437,0.000008944822,0.00004544207,0.00003107764,0.0003019527],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002505165,"threshold_uncertainty_score":0.01324874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003631423720009126,"score_gpt":0.2166059264179633,"score_spread":0.2129745026979542,"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."}}