{"id":"W4413458003","doi":"10.1109/iwbf63717.2025.11113424","title":"A Novel Hybrid Neural Embedding Extractor for Text Independent Speaker Verification","year":2025,"lang":"en","type":"article","venue":"","topic":"Speech Recognition and Synthesis","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Computer Research Institute of Montréal","funders":"","keywords":"Computer science; Extractor; Speaker verification; Speech recognition; Embedding; Speaker recognition; Artificial intelligence; Natural language processing; Pattern recognition (psychology); Engineering","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":[0.0009352606,0.001196005,0.0008609954,0.0008201333,0.0002799816,0.0005137341,0.001445784,0.0009361512,0.005014394],"category_scores_gemma":[0.00132699,0.000437956,0.0007578857,0.0005041737,0.0002888206,0.001821246,0.001539804,0.001242443,0.003769687],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004390742,"about_ca_system_score_gemma":0.000628068,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002489224,"about_ca_topic_score_gemma":0.005102172,"domain_scores_codex":[0.9993605,0.00009051055,0.00003506814,0.0002065715,0.0002290995,0.00007825822],"domain_scores_gemma":[0.9995924,0.00008385585,0.00004176166,0.00009310358,0.0001616125,0.00002740683],"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":[0.0003871388,0.0001370585,0.0007648896,0.0001097372,0.0001399054,0.0001222663,0.00005257604,0.01684113,0.104353,0.002225672,0.005197401,0.8696693],"study_design_scores_gemma":[0.00002875751,0.0001790264,0.001507037,0.00001904195,0.00007281839,0.0003049027,0.00002631941,0.8895882,0.0992289,0.00234073,0.006662116,0.00004218824],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01544678,0.00050731,0.9767376,0.00008705727,0.0001353514,0.00007822973,0.0003186658,0.005616634,0.001072437],"genre_scores_gemma":[0.3280366,0.0005161076,0.6487002,0.0003294811,0.0001498209,0.0002499156,0.0027391,0.0005358983,0.01874295],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005014394,"threshold_uncertainty_score":0.01677483,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0323791740611883,"score_gpt":0.294950542146094,"score_spread":0.2625713680849057,"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."}}