{"id":"W2087119585","doi":"10.1109/icassp.2010.5495503","title":"Score normalization in playback attack detection","year":2010,"lang":"en","type":"article","venue":"","topic":"Speech Recognition and Synthesis","field":"Computer Science","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Phrase; Utterance; Computer science; Speech recognition; Similarity (geometry); Normalization (sociology); Set (abstract data type); Pattern recognition (psychology); Thresholding; Task (project management); Artificial intelligence; Natural language processing; Detector","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":[0.0001358501,0.00004901941,0.00004933399,0.0001124251,0.00003493316,0.00007243022,0.0001860497,0.00005305126,0.0003366219],"category_scores_gemma":[0.00005078112,0.00004395524,0.00002050871,0.0002955476,0.00001041348,0.0003897104,0.00003329579,0.00008963615,0.0003724597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009559307,"about_ca_system_score_gemma":0.00001314696,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003312804,"about_ca_topic_score_gemma":0.001669584,"domain_scores_codex":[0.999522,0.00001797535,0.0001070569,0.0001489333,0.0001007923,0.0001032803],"domain_scores_gemma":[0.9996948,0.00003188615,0.00002365671,0.0001767068,0.00003640838,0.00003653865],"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":[0.000005371362,0.00008785897,0.0115498,0.000007355846,0.000003648418,0.00001016256,0.0002222719,0.00002675298,0.04606506,0.01151615,0.0005752443,0.9299303],"study_design_scores_gemma":[0.0005711483,0.00004908507,0.1156045,0.00001382042,0.000002473793,0.000070007,0.00003621631,0.3862308,0.4853896,0.002056839,0.009634847,0.0003407063],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5163494,0.000001546682,0.4548482,0.0002352985,0.0004629661,0.00007518771,1.639333e-7,0.0001367065,0.02789044],"genre_scores_gemma":[0.978099,0.000002340332,0.02122226,0.000262778,0.00003438777,0.000006751488,8.261907e-7,0.000003012536,0.000368607],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9295896,"threshold_uncertainty_score":0.478734,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02500157344188291,"score_gpt":0.2484622671024387,"score_spread":0.2234606936605557,"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."}}