{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["12(1)"],"submitter":["Si C"],"pubmed_abstract":["The lack of invariance problem in speech perception refers to a fundamental problem of how listeners deal with differences of speech sounds produced by various speakers. The current study is the first to test the contributions of mentally stored distributional information in normalization of prosodic cues. This study starts out by modelling distributions of acoustic cues from a speech corpus. We proceeded to conduct three experiments using both naturally produced lexical tones with estimated distributions and manipulated lexical tones with f0 values generated from simulated distributions. State of the art statistical techniques have been used to examine the effects of distribution parameters in normalization and identification curves with respect to each parameter. Based on the significant"],"journal":["Scientific reports"],"pagination":["14635"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9420126"],"repository":["biostudies-literature"],"pubmed_title":["Modelling representations in speech normalization of prosodic cues."],"pmcid":["PMC9420126"],"pubmed_authors":["Yang Y","Li B","Zhang C","Lau P","Si C"],"additional_accession":[]},"is_claimable":false,"name":"Modelling representations in speech normalization of prosodic cues.","description":"The lack of invariance problem in speech perception refers to a fundamental problem of how listeners deal with differences of speech sounds produced by various speakers. The current study is the first to test the contributions of mentally stored distributional information in normalization of prosodic cues. This study starts out by modelling distributions of acoustic cues from a speech corpus. We proceeded to conduct three experiments using both naturally produced lexical tones with estimated distributions and manipulated lexical tones with f0 values generated from simulated distributions. State of the art statistical techniques have been used to examine the effects of distribution parameters in normalization and identification curves with respect to each parameter. Based on the significant","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022 Aug","modification":"2025-04-04T13:46:37.126Z","creation":"2025-04-04T13:46:37.126Z"},"accession":"S-EPMC9420126","cross_references":{"pubmed":["36030274"],"doi":["10.1038/s41598-022-18838-w"]}}