{"id":"W7025109027","doi":"","title":"Using Auditory Models for Speaker Normalization in Speech Recognition","year":2022,"lang":"en","type":"article","venue":"Canadian acoustics","topic":"Advanced Numerical Methods in Computational Mathematics","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Normalization (sociology); Speaker recognition; Speech processing; Speaker identification; Pattern recognition (psychology); Computational auditory scene analysis","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":[0.0001493833,0.00008112792,0.00009825991,0.0001941961,0.00009504685,0.00001026152,0.00007759332,0.00003462295,0.00006066336],"category_scores_gemma":[0.0001214845,0.0001135153,0.00002095971,0.0002589338,0.00001168816,0.00009568669,0.00001313706,0.000130032,0.000003468748],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009357881,"about_ca_system_score_gemma":0.0001051247,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000228855,"about_ca_topic_score_gemma":0.000257298,"domain_scores_codex":[0.9993792,0.00002288839,0.0001817115,0.00009620414,0.0001099257,0.0002100823],"domain_scores_gemma":[0.999579,0.0001663904,0.00002741617,0.00008083691,0.00005160359,0.0000948164],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001534263,0.00000477398,0.00000505996,0.00004607237,0.000003844686,0.000006940645,0.00008121086,0.985429,0.0007555604,0.000236191,0.0004438161,0.01298598],"study_design_scores_gemma":[0.0001071859,0.000009516131,0.000036148,0.000009693872,0.000009108343,0.00001034513,0.00009756467,0.9096076,0.00003776812,0.08934914,0.0005990502,0.0001269153],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01872908,0.00003013135,0.9792886,0.00001351339,0.0008844131,0.0002354371,0.0001333819,0.00005207036,0.0006333867],"genre_scores_gemma":[0.2810957,0.000004722294,0.7184438,0.0001293793,0.0001626811,0.00004163262,0.00005947968,0.00004357405,0.00001902885],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2623666,"threshold_uncertainty_score":0.4629019,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0898020178580071,"score_gpt":0.2975509914898056,"score_spread":0.2077489736317985,"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."}}