{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001626437,0.0009796376,0.001118153,0.001539247,0.0007118243,0.001364172,0.001252322,0.001343629,0.005043265],"category_scores_gemma":[0.004241813,0.0005940169,0.0004101827,0.0004390757,0.0004109553,0.001494275,0.001058965,0.001468637,0.003472601],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006439105,"about_ca_system_score_gemma":0.0006800208,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009185572,"about_ca_topic_score_gemma":0.00105722,"domain_scores_codex":[0.998108,0.0002583602,0.0001412727,0.0002937051,0.001049247,0.0001494229],"domain_scores_gemma":[0.9980205,0.0007426747,0.0001960291,0.0003183979,0.0005909357,0.000131448],"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":[0.00145431,0.0002973496,0.003363417,0.000266542,0.0001306996,0.0005658596,0.000163197,0.008086451,0.3387848,0.005407499,0.00689806,0.6345819],"study_design_scores_gemma":[0.00009074852,0.0009332926,0.004015781,0.00005729057,0.0001112967,0.001652698,0.00005715779,0.6013531,0.3712145,0.002163948,0.01823756,0.0001125172],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02237159,0.0005591459,0.9633911,0.0001421352,0.0001404339,0.0002677421,0.0002179642,0.01142519,0.001484702],"genre_scores_gemma":[0.4359965,0.0004591561,0.5547857,0.0002836107,0.0001386051,0.0003238241,0.0006638245,0.0003531114,0.006995709],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005043265,"threshold_uncertainty_score":0.01687139,"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."}}