{"id":"W4296887698","doi":"10.18280/isi.270419","title":"Speech Coding Using Discrete Cosine Transform and Chaotic Map","year":2022,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Discrete cosine transform; Computer science; Speech coding; Data compression; Coding (social sciences); Speech recognition; Chaotic; Compression ratio; Algorithm; Artificial intelligence; Image (mathematics); Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0003260722,0.0004874418,0.000444755,0.001339376,0.0002266489,0.0004770508,0.0003607729,0.0003482235,0.001521078],"category_scores_gemma":[0.001282994,0.0001084784,0.0003631483,0.001231414,0.00026972,0.0006452608,0.0003991383,0.0003721034,0.0007017198],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003391868,"about_ca_system_score_gemma":0.0005454734,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004695129,"about_ca_topic_score_gemma":0.003530301,"domain_scores_codex":[0.9996406,0.00004655112,0.00002828978,0.00006675076,0.0001931525,0.00002474288],"domain_scores_gemma":[0.9996885,0.00007325589,0.00002385421,0.00005070437,0.0001513152,0.00001242687],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006333183,0.0001396553,0.001333114,0.0003722995,0.00006371205,0.0003995724,0.00009830326,0.09055522,0.117115,0.008779326,0.008198643,0.7723119],"study_design_scores_gemma":[0.00005204113,0.000221383,0.002806043,0.00003753565,0.00004041847,0.0004746945,0.00005925011,0.8789933,0.1018495,0.002897571,0.01251995,0.00004841353],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1596026,0.003605319,0.8201524,0.0007537873,0.0007433054,0.0003187888,0.001597396,0.003055108,0.01017138],"genre_scores_gemma":[0.6677001,0.002291566,0.3167481,0.0001676785,0.0002218684,0.0002480529,0.003564359,0.0001275829,0.008930787],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004695129,"threshold_uncertainty_score":0.009335577,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01840339391324438,"score_gpt":0.2384374870569289,"score_spread":0.2200340931436846,"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."}}