{"id":"W4416789334","doi":"10.1186/s13636-025-00435-0","title":"Accent-robust speech recognition for English in low-resource settings using Manifold Mixup","year":2025,"lang":"en","type":"article","venue":"EURASIP Journal on Audio Speech and Music Processing","topic":"Phonetics and Phonology Research","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"TIMIT; Robustness (evolution); Connectionism; Stress (linguistics); Speech corpus; Segmentation; Pattern recognition (psychology)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001114524,0.001120631,0.0007416801,0.0005891479,0.0005392819,0.0009635772,0.00100941,0.0007429792,0.003610007],"category_scores_gemma":[0.002262612,0.0004269512,0.0007518954,0.0005041807,0.0006981319,0.002470657,0.002365854,0.001306627,0.00290302],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003986107,"about_ca_system_score_gemma":0.0005437894,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001932769,"about_ca_topic_score_gemma":0.00327186,"domain_scores_codex":[0.9992607,0.000212988,0.00003531869,0.0002588507,0.0001440162,0.00008819536],"domain_scores_gemma":[0.9992241,0.0002867728,0.00004076052,0.0002265241,0.0001785176,0.00004331191],"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":[0.0006379865,0.0003401673,0.002076803,0.0001831987,0.0001667244,0.000316798,0.0004515463,0.1670164,0.08199301,0.010625,0.005486228,0.7307061],"study_design_scores_gemma":[0.00001796312,0.0002292352,0.001375334,0.00001343228,0.0000311705,0.0001870694,0.00008368702,0.9396148,0.04710645,0.007214517,0.004088348,0.00003788011],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05648958,0.0004574395,0.9362372,0.0001711719,0.00007291546,0.00008696911,0.0002083505,0.003594795,0.002681521],"genre_scores_gemma":[0.663053,0.0004347319,0.3244088,0.0002765518,0.0001149881,0.0002926545,0.00184137,0.0004772056,0.009100704],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003610007,"threshold_uncertainty_score":0.01207668,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05669892675248572,"score_gpt":0.3377159507968552,"score_spread":0.2810170240443695,"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."}}