{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002247088,0.00008781645,0.00009796161,0.0001231979,0.00008811703,0.0001915176,0.0003626862,0.00003202578,0.00011286],"category_scores_gemma":[0.0001172162,0.00007861549,0.00007776639,0.0001630442,0.000011762,0.0003141913,0.00006014336,0.0000572014,0.00006206213],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003980954,"about_ca_system_score_gemma":0.00004580779,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001405076,"about_ca_topic_score_gemma":0.000007101721,"domain_scores_codex":[0.9992037,0.0000177786,0.0001767878,0.0003009059,0.0001332982,0.0001674986],"domain_scores_gemma":[0.9993223,0.0002097224,0.00004361232,0.0002898613,0.00008852721,0.00004596538],"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":[0.0000293258,0.0002474915,0.0002711103,0.00003857736,0.0000400856,0.000003124571,0.00009980633,0.00002597318,0.05996446,0.08397011,0.005912714,0.8493972],"study_design_scores_gemma":[0.001092429,0.00004117094,0.01834725,0.0000468422,0.00001853566,0.00004280853,0.000100145,0.801258,0.1437083,0.003464228,0.03153765,0.0003426487],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02052522,0.00001383842,0.9658248,0.001144913,0.0004930891,0.0002451164,0.000005101906,0.0001580771,0.01158988],"genre_scores_gemma":[0.8255306,0.00000247556,0.1709229,0.0008382548,0.00003036577,0.00005450423,0.000004417793,0.000005030572,0.002611435],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8490546,"threshold_uncertainty_score":0.3205846,"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."}}