{"id":"W2109740207","doi":"10.1109/isccsp.2008.4537397","title":"A playback attack detector for speaker verification systems","year":2008,"lang":"en","type":"article","venue":"","topic":"Speech Recognition and Synthesis","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Detector; Similarity (geometry); Frame (networking); Set (abstract data type); Speech recognition; Cosine similarity; Feature (linguistics); Speaker verification; Utterance; Fast Fourier transform; Artificial intelligence; Pattern recognition (psychology); Speaker recognition; Algorithm; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001165891,0.00007023411,0.00009420211,0.00005176373,0.0001046224,0.00006641365,0.0002669257,0.00004123063,0.0000716156],"category_scores_gemma":[0.0000413548,0.00005905785,0.00005746123,0.0001310256,0.00001705783,0.0002111457,0.00002008863,0.00002573661,0.0006335099],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002367761,"about_ca_system_score_gemma":0.00002935328,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001255113,"about_ca_topic_score_gemma":0.000004074271,"domain_scores_codex":[0.9993268,0.00002320005,0.0001547773,0.000221337,0.0001314115,0.0001424996],"domain_scores_gemma":[0.9993929,0.0001122594,0.00004292639,0.0003000394,0.00009065124,0.00006119519],"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":[0.0001308957,0.0007631571,0.004990511,0.0002684458,0.0002464528,0.00006769141,0.002749238,0.0001720484,0.02828807,0.1103301,0.4116377,0.4403557],"study_design_scores_gemma":[0.001535725,0.0002267613,0.01482694,0.00004148731,0.00001667565,0.0005017325,0.000148883,0.5567641,0.06005944,0.0003476178,0.3647257,0.0008049284],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06686641,0.00003741252,0.9210923,0.0002971288,0.0004531111,0.0003384888,0.000004100942,0.0002516417,0.0106594],"genre_scores_gemma":[0.8614304,0.00001801573,0.1328434,0.0003112013,0.0001042952,0.0001108232,0.000003708801,0.000009796356,0.005168353],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.794564,"threshold_uncertainty_score":0.81427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09712723700519299,"score_gpt":0.2697773977651448,"score_spread":0.1726501607599518,"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."}}