{"id":"W2022663094","doi":"10.1145/1979742.1979700","title":"Ubiquitous voice synthesis","year":2011,"lang":"en","type":"article","venue":"","topic":"Speech Recognition and Synthesis","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Speech synthesis; Interactivity; Ubiquitous computing; Human–computer interaction; Embodied cognition; Phone; Production (economics); Multimedia; Speech recognition; Artificial intelligence; Linguistics","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001436339,0.00007282881,0.00008358514,0.00007304965,0.00005457122,0.00004700727,0.0005642106,0.00003683111,0.001830702],"category_scores_gemma":[0.00009428163,0.00005898115,0.0000546493,0.0001685609,0.00001893524,0.0002652897,0.00008655489,0.00003816237,0.003235876],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009624198,"about_ca_system_score_gemma":0.00001761086,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005842013,"about_ca_topic_score_gemma":0.00001356732,"domain_scores_codex":[0.9993536,0.00003646664,0.0001087263,0.0002066715,0.000128332,0.0001661374],"domain_scores_gemma":[0.9993634,0.0001260077,0.00002608715,0.0003600959,0.00004186649,0.00008249585],"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":[0.000003214824,0.0001085734,0.0002574576,0.00000417781,0.00001845039,0.00003970783,0.0004439776,2.607296e-8,0.0005214594,0.05681933,0.004682802,0.9371008],"study_design_scores_gemma":[0.0002190898,0.00008571825,0.01500372,0.00002946585,0.00002355598,0.0001634198,0.0002278606,0.006251761,0.9149655,0.02402329,0.03829845,0.0007082309],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.004553896,0.00001349035,0.317632,0.0003055015,0.0002391769,0.00005249673,5.794892e-7,0.0004568427,0.676746],"genre_scores_gemma":[0.5995426,0.00001117435,0.3968819,0.001087032,0.00004080688,0.00002515734,1.024192e-7,0.000007030359,0.00240429],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9363926,"threshold_uncertainty_score":0.9990817,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0597872934221393,"score_gpt":0.2251085287816754,"score_spread":0.1653212353595361,"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."}}