{"id":"W3127781879","doi":"10.48550/arxiv.2102.01640","title":"SPEAK WITH YOUR HANDS Using Continuous Hand Gestures to control Articulatory Speech Synthesizer","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Speech Recognition and Synthesis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Vocal tract; Gesture; Computer science; Speech recognition; Spline (mechanical); Kinematics; Speech production; Speech synthesis; Wrist; Acoustics; Artificial intelligence; Engineering; Anatomy","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002929244,0.0004479609,0.0006505494,0.0003530593,0.0002534195,0.00066285,0.001085914,0.0002975689,0.0001224042],"category_scores_gemma":[0.0001104836,0.0004458601,0.0002609558,0.0005720167,0.0001417935,0.0003315163,0.0007300921,0.0004521358,0.00008318232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002096421,"about_ca_system_score_gemma":0.0003386217,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001648036,"about_ca_topic_score_gemma":0.0001324313,"domain_scores_codex":[0.9974605,0.0002365305,0.0002508977,0.001356317,0.000190318,0.0005054414],"domain_scores_gemma":[0.9975585,0.0001869188,0.0002313845,0.001233664,0.0004132947,0.0003762557],"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":[0.002717646,0.00415528,0.05628829,0.001217436,0.00864489,0.1019689,0.01091876,0.6298407,0.04969944,0.04527512,0.004138017,0.08513556],"study_design_scores_gemma":[0.008474844,0.0006326596,0.01743173,0.002823577,0.001943512,0.001023922,0.002452979,0.856057,0.09502721,0.005171674,0.003244213,0.005716612],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6199,0.00004438743,0.3781612,0.000104213,0.0002400155,0.000299857,0.000009789709,0.0001400315,0.001100532],"genre_scores_gemma":[0.9844964,0.00001581343,0.01395068,0.0005065161,0.0001114359,0.000001860899,0.000004506767,0.00003295221,0.0008798062],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3645964,"threshold_uncertainty_score":0.9997993,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06921805763573322,"score_gpt":0.1929265297347166,"score_spread":0.1237084720989833,"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."}}