{"id":"W4402910001","doi":"10.1016/j.csl.2024.101723","title":"Speech Generation for Indigenous Language Education","year":2024,"lang":"en","type":"article","venue":"Computer Speech & Language","topic":"Multilingual Education and Policy","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University nuhelot'ine thaiyots'i nistameyimâkanak Blue Quills; National Research Council Canada","funders":"UK Research and Innovation","keywords":"Computer science; Indigenous; Natural language processing; Linguistics; Artificial intelligence; Speech recognition; Ecology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004621027,0.0001233936,0.0001194114,0.0001817082,0.0002879032,0.0003933281,0.0002369855,0.000107683,0.0004985866],"category_scores_gemma":[0.00007958284,0.0001229733,0.00009223609,0.0002943199,0.00004835996,0.0001810469,0.00002631343,0.0001197183,0.0002535256],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001621724,"about_ca_system_score_gemma":0.0009609936,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003758907,"about_ca_topic_score_gemma":0.001900494,"domain_scores_codex":[0.9989142,0.00008932453,0.0001856049,0.0002968736,0.0002119641,0.0003019633],"domain_scores_gemma":[0.9994191,0.00008381881,0.00004230892,0.0002259305,0.0000920362,0.0001368258],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000001630258,0.00005974856,0.00002022049,0.00003576177,0.00001147365,0.000008636373,0.2017266,0.000002541755,0.001298742,0.004048528,0.01434376,0.7784424],"study_design_scores_gemma":[0.0002386768,0.00007299041,0.0003068804,0.00007254747,0.00004092493,0.00002595277,0.02086171,0.005542043,0.007729248,0.0003359854,0.9643095,0.0004635828],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9454288,0.004112849,0.009598664,0.002449435,0.008070417,0.00111301,0.00003927576,0.0005813855,0.02860618],"genre_scores_gemma":[0.8776673,0.00007921863,0.04429961,0.003421417,0.02600224,0.0001087709,0.0003522832,0.00005821301,0.04801095],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9499657,"threshold_uncertainty_score":0.5682368,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04128638080843477,"score_gpt":0.4452927727766668,"score_spread":0.404006391968232,"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."}}