{"id":"W2059782236","doi":"10.1121/1.4783337","title":"Gesture controlled synthetic speech and song.","year":2009,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Human Motion and Animation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Gesture; Computer science; Speech recognition; Speech synthesis; Intelligibility (philosophy); Vocal tract; Rendering (computer graphics); Natural (archaeology); Human–computer interaction; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007368441,0.0004781364,0.0002628987,0.0003230193,0.0002511094,0.0009802898,0.0008017439,0.0005483065,0.02164191],"category_scores_gemma":[0.001069864,0.0001513116,0.0003688564,0.0002172592,0.0005348292,0.0008163226,0.0007438616,0.0004256981,0.005002956],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002531653,"about_ca_system_score_gemma":0.0002168432,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005414057,"about_ca_topic_score_gemma":0.0009548622,"domain_scores_codex":[0.9994649,0.0001229556,0.00002789418,0.0001160248,0.0002373823,0.00003090737],"domain_scores_gemma":[0.9995455,0.0001699976,0.00002588647,0.0001421598,0.00006289545,0.00005348379],"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":[0.0005861068,0.0002323099,0.001040046,0.001095529,0.00008053037,0.0004167242,0.0006850731,0.01313686,0.3786248,0.03598805,0.01183528,0.5562788],"study_design_scores_gemma":[0.0001744617,0.001143392,0.003665534,0.0001891979,0.00007732993,0.002101671,0.0003379182,0.08111431,0.3110326,0.01198592,0.5880433,0.0001344092],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08566912,0.004411441,0.7715164,0.0005790993,0.001272744,0.0006861481,0.001606745,0.0085599,0.1256983],"genre_scores_gemma":[0.4606868,0.002658714,0.4204611,0.0003742452,0.0002524019,0.0006378559,0.004361154,0.00137114,0.1091967],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02164191,"threshold_uncertainty_score":0.07239938,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00623154770182761,"score_gpt":0.2151930728754407,"score_spread":0.2089615251736131,"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."}}