{"id":"W2149564831","doi":"10.1109/ccece.1993.332209","title":"A DSP realization of a CELP testbench","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Data Compression Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Code-excited linear prediction; Computer science; Realization (probability); Modular design; Software; Process (computing); Digital signal processing; Linear predictive coding; Code (set theory); Simple (philosophy); Computer hardware; Speech coding; Speech recognition; Programming language","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006989863,0.0007488047,0.0003862283,0.0008862671,0.000316939,0.0009794576,0.001951285,0.00067978,0.01562555],"category_scores_gemma":[0.002413967,0.0002730492,0.0002363437,0.0003229897,0.0003400448,0.0008102221,0.0004847372,0.0007612609,0.005054578],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004344133,"about_ca_system_score_gemma":0.0007009512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008221251,"about_ca_topic_score_gemma":0.0004964087,"domain_scores_codex":[0.9992471,0.0001353882,0.00005689222,0.0001078955,0.0003627088,0.00009004571],"domain_scores_gemma":[0.998544,0.0005018075,0.00008092641,0.000285965,0.0005022917,0.00008501081],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001605042,0.0005623506,0.002652231,0.001133735,0.0001080755,0.00202106,0.000668287,0.05394797,0.4842764,0.03700739,0.01669885,0.3993186],"study_design_scores_gemma":[0.0003899003,0.001772883,0.001621306,0.0001473903,0.00006380841,0.001534456,0.0001068743,0.2609311,0.6315585,0.003864242,0.09793212,0.00007740362],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04602793,0.0001807632,0.9110174,0.0001490316,0.0001701524,0.0004997941,0.001006524,0.02045914,0.02048928],"genre_scores_gemma":[0.6166087,0.0002485433,0.3558356,0.000306227,0.00009008287,0.001187293,0.003790862,0.001765799,0.02016703],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01562555,"threshold_uncertainty_score":0.05227274,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02456207456647535,"score_gpt":0.238245607959889,"score_spread":0.2136835333934136,"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."}}