{"id":"W2137996830","doi":"10.1109/tsa.2005.851941","title":"A blind channel identification-based two-stage approach to separation and dereverberation of speech signals in a reverberant environment","year":2005,"lang":"en","type":"article","venue":"IEEE Transactions on Speech and Audio Processing","topic":"Blind Source Separation Techniques","field":"Computer Science","cited_by":103,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec","funders":"","keywords":"Reverberation; Blind signal separation; MIMO; Robustness (evolution); Computer science; Speech recognition; Source separation; Interference (communication); Channel (broadcasting); Signal processing; Acoustics; Algorithm; Telecommunications; Physics","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":[0.0006145007,0.0001712396,0.0002059579,0.0004026566,0.0001663795,0.0002113772,0.0001564331,0.00008037072,0.000003539718],"category_scores_gemma":[0.000005378446,0.0001769327,0.00003450446,0.0004241631,0.00004510915,0.0007705496,0.000003684506,0.0001654591,0.000008398028],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007300876,"about_ca_system_score_gemma":0.00008390567,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003596737,"about_ca_topic_score_gemma":0.0000561991,"domain_scores_codex":[0.9985083,0.00009188668,0.0004478434,0.0004747871,0.0002995619,0.0001775746],"domain_scores_gemma":[0.9993989,0.00004681026,0.0001644547,0.0002381,0.00006390897,0.00008785279],"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":[0.0001351287,0.0006977023,0.00002930424,0.0001969462,0.00001912435,0.000003052318,0.005741504,0.2892268,0.1502789,0.0001892473,0.00003706545,0.5534452],"study_design_scores_gemma":[0.000768218,0.00008370834,0.0001580366,0.00008474734,0.00001018864,0.00001054338,0.00006542321,0.3341084,0.6641907,0.0002081228,0.0001145023,0.0001973414],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08473204,0.0000797886,0.9134051,0.0009650953,0.00001774718,0.000533304,0.00000696039,0.00007016841,0.0001897925],"genre_scores_gemma":[0.8266534,0.00003129181,0.1726519,0.0003417451,0.00001830867,0.00008449358,0.000003395658,0.00001019824,0.0002053197],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7419213,"threshold_uncertainty_score":0.7215106,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02512904293596091,"score_gpt":0.2882898073889731,"score_spread":0.2631607644530122,"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."}}