{"id":"W2606346295","doi":"10.1080/09588221.2017.1312463","title":"The pedagogical use of mobile speech synthesis (TTS): focus on French liaison","year":2017,"lang":"en","type":"article","venue":"Computer Assisted Language Learning","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":73,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Concordia University","funders":"","keywords":"Pronunciation; Psychology; Conversation; Consonant; Vowel; Linguistics; Categorization; Computer science; Mathematics education; Speech recognition; Communication; Artificial intelligence","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":[0.001399034,0.0005965829,0.0004585493,0.0005239982,0.0005068627,0.0007020296,0.0004597809,0.0006992102,0.002363876],"category_scores_gemma":[0.0049349,0.0001489614,0.0004177984,0.0003588772,0.0005954278,0.0006192048,0.0008464238,0.0003887089,0.0004082791],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006437644,"about_ca_system_score_gemma":0.000777619,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003127228,"about_ca_topic_score_gemma":0.00492284,"domain_scores_codex":[0.9983199,0.000974482,0.00007156121,0.0002394018,0.0002050884,0.0001896036],"domain_scores_gemma":[0.995914,0.002937844,0.0003412643,0.0002261222,0.0003234124,0.000257313],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.003154523,0.01517605,0.0935432,0.002882033,0.000215371,0.002538119,0.07204917,0.00256115,0.1351493,0.001634423,0.0009212979,0.6701753],"study_design_scores_gemma":[0.0008282255,0.1248889,0.627015,0.0007702871,0.001008069,0.005076428,0.05463006,0.006113935,0.1393861,0.001430093,0.03863983,0.0002131486],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996796,0.0002624712,0.001068869,0.00008827163,0.000008760303,0.0000974489,0.00002103187,0.00002041968,0.001636776],"genre_scores_gemma":[0.9944754,0.0006384,0.003219962,0.00008193845,0.00002731645,0.0002073993,0.0000577521,0.0000102272,0.001281631],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003127228,"threshold_uncertainty_score":0.007907987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0616561466476619,"score_gpt":0.3100860936310043,"score_spread":0.2484299469833424,"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."}}