{"id":"W4285102625","doi":"10.1109/dslw53931.2022.9820506","title":"Practical Cognitive Speech Compression","year":2022,"lang":"en","type":"article","venue":"","topic":"Advanced Data Compression Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Codec; Computer science; Speech recognition; Speech coding; PSQM; Encoder; Telephony; Quantization (signal processing); Linear predictive coding; Computer vision; Telecommunications","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002187325,0.00009256206,0.0001035461,0.00008169219,0.0003300048,0.00005693779,0.0007393773,0.00001891436,0.0008903371],"category_scores_gemma":[0.00009228475,0.00008155282,0.00003190335,0.0003022912,0.0000298253,0.0007217205,0.003118189,0.0003145246,0.00006479801],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003899014,"about_ca_system_score_gemma":0.00005182397,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008908365,"about_ca_topic_score_gemma":4.065149e-7,"domain_scores_codex":[0.9986383,0.000172032,0.0001504144,0.0003780504,0.0004663542,0.0001948091],"domain_scores_gemma":[0.9990025,0.0003035387,0.00007550402,0.0004852599,0.00005484257,0.00007835111],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005709952,0.0006388858,0.000235505,0.000006899528,0.00001610943,0.0004419429,0.0002116376,0.0000322111,0.007951992,0.3997376,0.3258659,0.2648043],"study_design_scores_gemma":[0.00124213,0.0007072581,0.0006750348,0.0000450913,0.00001166301,0.001114548,0.0005354516,0.1144044,0.27371,0.07392517,0.5327003,0.0009289174],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0004546928,0.00001900021,0.9815804,0.001502041,0.0001720245,0.0001802414,0.00001066845,0.0008278532,0.01525301],"genre_scores_gemma":[0.2786149,0.000005020201,0.7186639,0.001610027,0.00002226383,0.00009397732,0.00001586358,0.000008478078,0.0009655633],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3258124,"threshold_uncertainty_score":0.9748567,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04486009747172853,"score_gpt":0.3631831777002367,"score_spread":0.3183230802285082,"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."}}