{"id":"W4399911677","doi":"10.48550/arxiv.2406.14294","title":"DASB - Discrete Audio and Speech Benchmark","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Data Compression Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Alliance de recherche numérique du Canada","keywords":"Benchmark (surveying); Speech recognition; Computer science; Geography; Cartography","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005597084,0.002700516,0.001620088,0.002447927,0.0009920823,0.002265374,0.002925619,0.002533992,0.009964703],"category_scores_gemma":[0.0181916,0.000430925,0.001085854,0.002331137,0.00141944,0.002552825,0.003998331,0.002643325,0.009238746],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001312144,"about_ca_system_score_gemma":0.002033873,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006440939,"about_ca_topic_score_gemma":0.008277616,"domain_scores_codex":[0.9942647,0.001807299,0.0005234507,0.001092719,0.001838057,0.0004738682],"domain_scores_gemma":[0.9943667,0.002342767,0.0002183177,0.001426095,0.001220199,0.0004257765],"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":[0.005463991,0.002025245,0.008691399,0.003776734,0.000676325,0.0009077085,0.0004006346,0.1726428,0.03008469,0.01529875,0.2890255,0.4710062],"study_design_scores_gemma":[0.001489562,0.002760653,0.0148123,0.0005436142,0.0002024482,0.001727187,0.001041448,0.7383884,0.07407168,0.04326812,0.121388,0.0003065523],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.3920379,0.01390116,0.3218968,0.004274002,0.004259993,0.002346451,0.1417391,0.06430858,0.05523594],"genre_scores_gemma":[0.4970284,0.001875655,0.1624975,0.001132166,0.0003936483,0.002218386,0.3113161,0.004115528,0.01942257],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.009964703,"threshold_uncertainty_score":0.03333527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04544223868279033,"score_gpt":0.2083206412231259,"score_spread":0.1628784025403355,"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."}}