{"id":"W2349982397","doi":"","title":"One Voice Activity Detection Algorithm Base on Slip Window","year":2006,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Advanced Algorithms and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Robustness (evolution); Waveform; Speech recognition; Algorithm; Telecommunications","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004077121,0.0001892876,0.0001471818,0.0001022418,0.000226466,0.00005164234,0.0001782139,0.00008355027,0.00001124419],"category_scores_gemma":[1.552455e-7,0.0002285488,0.00007044716,0.0003860929,0.00003306725,0.0001216457,0.00002342649,0.0002184556,0.0004214705],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001167734,"about_ca_system_score_gemma":0.000008302799,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004322753,"about_ca_topic_score_gemma":0.00002525065,"domain_scores_codex":[0.9990938,0.000009935966,0.0001915319,0.0003307906,0.0001133014,0.0002606168],"domain_scores_gemma":[0.9994218,0.0000532673,0.00004221513,0.000361517,0.00004974509,0.00007147031],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000001121909,0.0001778884,0.000004023487,0.0000126722,0.00001350498,2.957204e-7,0.00001024336,0.01524068,0.1219721,0.0004421235,0.000398012,0.8617273],"study_design_scores_gemma":[0.0005418464,0.00003368043,0.008239509,0.00001728198,0.00003127622,0.00001200984,0.00000759205,0.1327381,0.3492818,0.003172193,0.5053614,0.0005633],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008715956,0.00005211928,0.9879297,0.0001136408,0.00002869346,0.0006777565,0.00007253651,0.0007475932,0.001662014],"genre_scores_gemma":[0.4777701,0.00001795931,0.5183779,0.0001352578,0.001290029,0.001944814,0.0001100962,0.00008741707,0.0002663833],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.861164,"threshold_uncertainty_score":0.931995,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005947158958493704,"score_gpt":0.1999597611867799,"score_spread":0.1940126022282862,"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."}}