{"id":"W2994436455","doi":"","title":"Toward better automatic speech recognition","year":2005,"lang":"en","type":"article","venue":"Canadian acoustics","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Speech recognition; Computer science; Cepstrum; Mel-frequency cepstrum; Speaker recognition; Discrete cosine transform; Linear prediction; Speech processing; Vowel; Pattern recognition (psychology); Invariant (physics); Artificial intelligence; Feature extraction; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.009159703,0.001555926,0.001553138,0.002125625,0.0007414098,0.004499813,0.002668614,0.004859898,0.01773162],"category_scores_gemma":[0.01221158,0.0008560519,0.001000248,0.001579744,0.001775231,0.006858231,0.003333209,0.003721967,0.02500865],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00135862,"about_ca_system_score_gemma":0.00184431,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002032551,"about_ca_topic_score_gemma":0.001833705,"domain_scores_codex":[0.9945838,0.001401293,0.0004330434,0.001461052,0.00185647,0.0002644499],"domain_scores_gemma":[0.9888671,0.002132213,0.0003412953,0.002208277,0.006118962,0.0003322696],"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":[0.0002224994,0.0002927876,0.0008516309,0.000664601,0.00007048262,0.00008265369,0.0003822861,0.007508628,0.06845951,0.09133388,0.03984606,0.7902848],"study_design_scores_gemma":[0.0001130896,0.0005190625,0.002466713,0.0006298008,0.0001137675,0.0007358741,0.0005088681,0.18166,0.07527775,0.08959923,0.6481526,0.0002232515],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005131833,0.00989092,0.9559253,0.007613041,0.001078793,0.0001202677,0.0003859185,0.005121517,0.01473228],"genre_scores_gemma":[0.0372747,0.008745077,0.9182983,0.003012008,0.001316695,0.0002231172,0.001982288,0.0005802447,0.02856756],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01773162,"threshold_uncertainty_score":0.05931824,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02507932776361542,"score_gpt":0.2257324399258334,"score_spread":0.200653112162218,"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."}}