{"id":"W4392359077","doi":"10.18280/ria.380108","title":"Audio-Visual Source Separation Based Fusion Techniques","year":2024,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Baghdad","keywords":"Audio visual; Separation (statistics); Computer science; Fusion; Source separation; Artificial intelligence; Multimedia; Machine learning; Linguistics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008637873,0.00154679,0.001122065,0.001207583,0.0003267207,0.00113337,0.001636061,0.001283095,0.003595973],"category_scores_gemma":[0.001448917,0.0004366294,0.00146773,0.0009431693,0.0004440281,0.001831698,0.002797653,0.001761149,0.002184182],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005834336,"about_ca_system_score_gemma":0.0008143752,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001964409,"about_ca_topic_score_gemma":0.002264141,"domain_scores_codex":[0.9994023,0.00007432133,0.00003223149,0.0001627738,0.0002511277,0.0000771982],"domain_scores_gemma":[0.9996217,0.0000820625,0.00004076278,0.00006600306,0.0001615308,0.00002783924],"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":[0.0004022384,0.0001993284,0.0006162044,0.000223071,0.0001949129,0.0001441185,0.0001073053,0.1167655,0.07175707,0.009496626,0.004650732,0.7954428],"study_design_scores_gemma":[0.00001715432,0.00009465841,0.0004451335,0.00002862726,0.00005615042,0.0001613229,0.00002551456,0.95885,0.02780353,0.008091361,0.004400214,0.0000262345],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004775204,0.000617011,0.991414,0.0001158872,0.00007487467,0.00003440792,0.000100513,0.001129076,0.001739158],"genre_scores_gemma":[0.4320402,0.001704343,0.5497238,0.0005297487,0.0002660926,0.0002045164,0.001449289,0.0003447239,0.01373717],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003595973,"threshold_uncertainty_score":0.01202977,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02718045155575837,"score_gpt":0.3159570186375922,"score_spread":0.2887765670818338,"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."}}