{"id":"W4402671201","doi":"10.18653/v1/2024.arabicnlp-1.11","title":"Towards Zero-Shot Text-To-Speech for Arabic Dialects","year":2024,"lang":"en","type":"article","venue":"","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Alliance de recherche numérique du Canada; Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Zero (linguistics); Arabic; Computer science; Natural language processing; Speech recognition; Artificial intelligence; Linguistics; Philosophy","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001675846,0.001533394,0.000944417,0.00105974,0.0006021386,0.00147736,0.001470443,0.001500997,0.003482325],"category_scores_gemma":[0.005011464,0.0004106549,0.001139333,0.0004466567,0.0005626995,0.00217294,0.001762388,0.001863441,0.004991381],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006993398,"about_ca_system_score_gemma":0.0008587664,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005844029,"about_ca_topic_score_gemma":0.007601742,"domain_scores_codex":[0.9989151,0.0003790665,0.00005566234,0.0004314615,0.0001416652,0.00007714608],"domain_scores_gemma":[0.9976871,0.001243985,0.00007811266,0.0003303052,0.0005210876,0.0001393775],"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":[0.002446226,0.0005329385,0.004861469,0.0008383886,0.0003210515,0.0006931141,0.001109684,0.07903639,0.105529,0.005206396,0.0239381,0.7754872],"study_design_scores_gemma":[0.00006362856,0.0003310046,0.002459951,0.00006918767,0.00009378712,0.0004899831,0.0004270872,0.9358719,0.04381321,0.007553259,0.008761904,0.0000651333],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1646427,0.003061638,0.797029,0.0009278082,0.0009263033,0.0003065375,0.004122627,0.02313873,0.005844717],"genre_scores_gemma":[0.6031367,0.0009162388,0.3666516,0.0006843365,0.0003667878,0.0003267984,0.01575133,0.0012064,0.0109599],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005844029,"threshold_uncertainty_score":0.01164949,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02452379365379888,"score_gpt":0.3145577619983406,"score_spread":0.2900339683445418,"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."}}