{"id":"W2127390035","doi":"10.1109/89.902283","title":"Synthetic stereo acoustic echo cancellation structure for multiple participant VoIP conferences","year":2001,"lang":"en","type":"article","venue":"IEEE Transactions on Speech and Audio Processing","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Monaural; Spatialization; Echo (communications protocol); Computer science; Stereophonic sound; Teleconference; Loudspeaker; Voice over IP; Reverberation; Speech recognition; Channel (broadcasting); Artificial intelligence; Acoustics; Telecommunications; The Internet","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001812223,0.0002845878,0.0003008761,0.0001788885,0.0006416928,0.0005604528,0.0003155326,0.0001276083,0.00001805275],"category_scores_gemma":[0.00002500108,0.0002487557,0.00007326442,0.0004118717,0.00009829453,0.0007472726,0.000003983206,0.0002354995,0.000004362447],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004984541,"about_ca_system_score_gemma":0.0002439659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002458052,"about_ca_topic_score_gemma":0.0002882315,"domain_scores_codex":[0.9981645,0.00003483424,0.0003493799,0.0006388614,0.0002718878,0.0005404932],"domain_scores_gemma":[0.9990274,0.0001695217,0.0001767462,0.000271623,0.0001718828,0.0001828078],"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":[0.00007915039,0.00008667655,0.000247766,0.0001879403,0.00002499105,0.00001292835,0.000818462,0.005544006,0.05608052,0.000007371472,0.00003620439,0.936874],"study_design_scores_gemma":[0.001282275,0.000272585,0.0002063098,0.0004584094,0.0001121073,0.000172208,0.0003819682,0.1733841,0.8196943,0.002138117,0.001282374,0.0006152962],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.121203,0.00037757,0.8767616,0.0005885961,0.0003342558,0.0003054403,0.00001693604,0.0003149302,0.00009758688],"genre_scores_gemma":[0.9532356,0.0000988606,0.04601177,0.0002667049,0.00009616846,0.00004643506,0.00000200963,0.00002855923,0.0002139295],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9362587,"threshold_uncertainty_score":0.9999965,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0403782802899136,"score_gpt":0.2751404288449312,"score_spread":0.2347621485550176,"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."}}