{"id":"W2130186711","doi":"10.1109/icassp.1994.389241","title":"Low-complexity encoding of speech LSF parameters using constrained-storage TSVQ","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Data Compression Techniques","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Vector quantization; Computational complexity theory; Algorithm; Encoding (memory); Speech coding; Computer science; Quantization (signal processing); Coding (social sciences); Theoretical computer science; Tree (set theory); Linear predictive coding; Computation; Speech recognition; Mathematics; Artificial intelligence; Statistics","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":[0.00019706,0.0001399086,0.0002087757,0.0001342702,0.0001053216,0.00005033375,0.000930463,0.0000402839,0.0002392963],"category_scores_gemma":[0.00008092541,0.0001245169,0.00006133171,0.0003882723,0.0002093221,0.0009415625,0.0004189076,0.0001106691,0.00001797154],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004055471,"about_ca_system_score_gemma":0.00001150136,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003668645,"about_ca_topic_score_gemma":0.000002058646,"domain_scores_codex":[0.9986796,0.00005834701,0.0003349369,0.0003722301,0.0002785262,0.0002763288],"domain_scores_gemma":[0.9987548,0.0001445426,0.0001486376,0.0007812302,0.00007322541,0.00009753705],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000007617578,0.000234089,0.0008930693,0.00004542658,0.00001559348,0.00007920224,0.000501939,0.00144241,0.6372216,0.1710372,0.0005107362,0.188011],"study_design_scores_gemma":[0.0002024464,0.00004598885,0.0001107503,0.00004296193,0.000002138845,0.00006265935,0.00003466973,0.32735,0.6565545,0.01522701,0.0001574526,0.0002094235],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1717126,0.000009393166,0.8237432,0.0000792535,0.00006234258,0.0001232445,0.000003554692,0.0003842836,0.003882135],"genre_scores_gemma":[0.500969,0.000002426487,0.498908,0.00008883313,0.000006170458,0.000001824402,4.934297e-7,0.000003629553,0.00001956809],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.3292564,"threshold_uncertainty_score":0.507765,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0976161355753597,"score_gpt":0.3030968229210413,"score_spread":0.2054806873456816,"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."}}