{"id":"W4406080107","doi":"10.1016/j.rineng.2025.103943","title":"Automated speech therapy through personalized pronunciation correction using reinforcement learning and large language models","year":2025,"lang":"en","type":"article","venue":"Results in Engineering","topic":"Speech Recognition and Synthesis","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pronunciation; Computer science; Reinforcement learning; Natural language processing; Reinforcement; Speech therapy; Speech recognition; Artificial intelligence; Linguistics; Psychology; Audiology; Medicine; Social 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003378942,0.00009801624,0.000115807,0.0001686833,0.0000621828,0.00007694454,0.00008797126,0.00005774612,0.000002930697],"category_scores_gemma":[0.0001418719,0.00009887595,0.00002403069,0.0003918605,0.000005194741,0.0003559299,0.00004386876,0.0001232754,0.000001374547],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001232192,"about_ca_system_score_gemma":0.00002625561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000621216,"about_ca_topic_score_gemma":0.000005099411,"domain_scores_codex":[0.9992457,0.00003328806,0.0002012586,0.0002068487,0.0001344294,0.0001784944],"domain_scores_gemma":[0.9997181,0.00008079973,0.00004755404,0.0001023535,0.0000340456,0.00001717837],"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":[0.0001214568,0.000092521,0.0002524364,0.0001111393,0.00006494515,0.00003936201,0.01622363,0.7638669,0.02302085,0.005460517,0.0001202323,0.190626],"study_design_scores_gemma":[0.0009091689,0.00001278366,0.0001180928,0.0001412855,0.000002050518,0.00000576542,0.0002012606,0.987318,0.01043078,0.00003919889,0.0007221202,0.00009948573],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08439875,0.0002964136,0.9113637,0.00005267528,0.0003118242,0.0001984865,9.023625e-7,0.0005836612,0.002793553],"genre_scores_gemma":[0.9574351,0.0001355008,0.04199276,0.00006002183,0.00002070334,0.00001208055,0.000005788477,0.000007808921,0.0003302031],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8730364,"threshold_uncertainty_score":0.4032044,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01881285815148709,"score_gpt":0.2752923702156232,"score_spread":0.2564795120641362,"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."}}