{"id":"W1993505392","doi":"10.1121/1.4779035","title":"A human vocal utterance corpus for perceptual and acoustic analysis of speech, singing, and intermediate vocalizations","year":2002,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Music and Audio Processing","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Utterance; Singing; Annotation; Computer science; Speech recognition; Speech corpus; Perception; Natural language processing; Artificial intelligence; Speech synthesis; Acoustics; Psychology","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":[0.004007318,0.0009877797,0.001050428,0.005957857,0.002562646,0.001465034,0.001409682,0.001328339,0.01831913],"category_scores_gemma":[0.0143314,0.0004795632,0.0006130449,0.003857908,0.001048801,0.001663982,0.002793484,0.001517604,0.0100336],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008625847,"about_ca_system_score_gemma":0.00310244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006392832,"about_ca_topic_score_gemma":0.01104257,"domain_scores_codex":[0.9944739,0.001648792,0.0009127361,0.0009313123,0.001785692,0.000247581],"domain_scores_gemma":[0.9833907,0.005172905,0.0007237578,0.003255626,0.006639336,0.0008177367],"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":[0.001304793,0.001475691,0.01159436,0.004507729,0.000140237,0.001713608,0.01074198,0.001834908,0.1664728,0.007667262,0.1861747,0.6063719],"study_design_scores_gemma":[0.0003365004,0.001091436,0.2030802,0.0008756887,0.0002263982,0.004665334,0.006193471,0.01205126,0.05100048,0.00387508,0.7161633,0.0004409072],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1952563,0.003739555,0.4280395,0.00136254,0.002366435,0.01901186,0.2651376,0.01917133,0.06591497],"genre_scores_gemma":[0.1143551,0.0008969318,0.50974,0.0004021959,0.0004377126,0.02645561,0.3263689,0.002010803,0.0193328],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01831913,"threshold_uncertainty_score":0.06128359,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01779515894985953,"score_gpt":0.2589692334632795,"score_spread":0.24117407451342,"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."}}