{"id":"W1971890869","doi":"10.1109/isspit.2007.4458152","title":"Speaker Accent Classification Using Distance Metric Learning Approach","year":2007,"lang":"en","type":"article","venue":"","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Pronunciation; Computer science; Stress (linguistics); Substitution (logic); Variation (astronomy); Speech recognition; Artificial intelligence; Natural language processing; Metric (unit); Euclidean distance; Class (philosophy); Process (computing); Space (punctuation); Linguistics; 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":[0.001861523,0.0007713469,0.001278325,0.002286454,0.0005173094,0.001052878,0.001361664,0.000951649,0.001517493],"category_scores_gemma":[0.003168153,0.0002056147,0.00068834,0.001574941,0.0003284133,0.001060342,0.000982014,0.0008326255,0.001156327],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000528219,"about_ca_system_score_gemma":0.0006841456,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002529375,"about_ca_topic_score_gemma":0.001748015,"domain_scores_codex":[0.9979704,0.0006065504,0.0001731656,0.0004611752,0.0006645484,0.0001241241],"domain_scores_gemma":[0.9985086,0.0004582391,0.0000937739,0.0001667408,0.0006989652,0.00007366705],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002573717,0.000187269,0.003630033,0.0001055542,0.0001685592,0.00009163716,0.0001676539,0.05862109,0.01403136,0.003935117,0.003967441,0.9148368],"study_design_scores_gemma":[0.00001618857,0.000108162,0.002585669,0.000007883587,0.00002721046,0.0001332045,0.00007650803,0.9825439,0.007748615,0.003916329,0.002799127,0.00003721269],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03102174,0.0004204726,0.9655343,0.0001145412,0.00009454279,0.00008955708,0.0001408724,0.001107265,0.001476735],"genre_scores_gemma":[0.4310954,0.0003967945,0.5625549,0.00008744552,0.0001662137,0.0002306823,0.001056737,0.0001288665,0.004283015],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002529375,"threshold_uncertainty_score":0.00984484,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05348860360179948,"score_gpt":0.2954239290423056,"score_spread":0.2419353254405061,"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."}}