{"id":"W2140046090","doi":"10.1109/icassp.2008.4518622","title":"Speaker diarization of French broadcast news","year":2008,"lang":"en","type":"article","venue":"Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing","topic":"Speech Recognition and Synthesis","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Computer Research Institute of Montréal","funders":"","keywords":"Speaker diarisation; Computer science; Mel-frequency cepstrum; Cluster analysis; Speech recognition; Feature (linguistics); Test set; Word error rate; Set (abstract data type); Hierarchical clustering; Pattern recognition (psychology); Speaker recognition; Artificial intelligence; Segmentation; Feature extraction","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":[0.00245644,0.001419349,0.0009699423,0.002747131,0.0008668148,0.0008544376,0.0005403007,0.0005959058,0.00291102],"category_scores_gemma":[0.004140923,0.0001706232,0.0008912117,0.001245449,0.0003059796,0.0004765204,0.0005935873,0.0005568808,0.001745312],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008228822,"about_ca_system_score_gemma":0.00038036,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02408714,"about_ca_topic_score_gemma":0.02202058,"domain_scores_codex":[0.9977126,0.0006956104,0.0001300751,0.0005820552,0.0005751061,0.0003045506],"domain_scores_gemma":[0.996699,0.001162144,0.0001255366,0.0002979361,0.001530887,0.0001842782],"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":[0.003236639,0.000385667,0.01893419,0.0008484105,0.0006388583,0.0006208992,0.001367217,0.01457411,0.1384622,0.0004945425,0.01142191,0.8090153],"study_design_scores_gemma":[0.000404804,0.003106911,0.3285583,0.00008697405,0.001361529,0.00263837,0.001979558,0.1621991,0.4451111,0.0006392823,0.05347812,0.0004360371],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9043772,0.003956266,0.06497737,0.000306654,0.0005046958,0.0003773035,0.005948782,0.007906181,0.01164567],"genre_scores_gemma":[0.9093568,0.0009070985,0.05093703,0.0001413393,0.0002280924,0.0001593753,0.02457359,0.0006093978,0.01308736],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02408714,"threshold_uncertainty_score":0.04789388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05214884939631418,"score_gpt":0.2664301578707716,"score_spread":0.2142813084744574,"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."}}