{"title":"韵律感知的个体差异与趋同模式","authors":"Joseph Roy, J. Cole, Tim Mahrt","doi":"10.5334/LABPHON.108","DOIUrl":null,"url":null,"abstract":"The challenge of prosodic annotation is reflected in commonly reported variability among trained annotators in the assignment of prosodic labels. The present study examines individual differences in the perception of prosody through the lens of prosodic annotation. First, Generalized Additive Mixed Models (GAMMs) reveal the non-linear pattern of some acoustic cues on the perception of prosodic features. Second, these same models reveal that while some of the untrained annotators are using these cues to determine prosodic features, the magnitude of effect differs quite dramatically across the annotators. Finally, the trained annotators follow the same cues as subsets of the untrained annotators, but present a much stronger effect for many of the cues. The findings show that while prosody perception is systemically related to acoustic and contextual cues, there are also individual differences that are limited to the selection and magnitude of the factors that influence prosodic rating, and the relative weighting among those factors.","PeriodicalId":45128,"journal":{"name":"Laboratory Phonology","volume":"8 1","pages":"22"},"PeriodicalIF":1.3000,"publicationDate":"2017-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"24","resultStr":"{\"title\":\"Individual differences and patterns of convergence in prosody perception\",\"authors\":\"Joseph Roy, J. Cole, Tim Mahrt\",\"doi\":\"10.5334/LABPHON.108\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The challenge of prosodic annotation is reflected in commonly reported variability among trained annotators in the assignment of prosodic labels. The present study examines individual differences in the perception of prosody through the lens of prosodic annotation. First, Generalized Additive Mixed Models (GAMMs) reveal the non-linear pattern of some acoustic cues on the perception of prosodic features. Second, these same models reveal that while some of the untrained annotators are using these cues to determine prosodic features, the magnitude of effect differs quite dramatically across the annotators. Finally, the trained annotators follow the same cues as subsets of the untrained annotators, but present a much stronger effect for many of the cues. The findings show that while prosody perception is systemically related to acoustic and contextual cues, there are also individual differences that are limited to the selection and magnitude of the factors that influence prosodic rating, and the relative weighting among those factors.\",\"PeriodicalId\":45128,\"journal\":{\"name\":\"Laboratory Phonology\",\"volume\":\"8 1\",\"pages\":\"22\"},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2017-09-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"24\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Laboratory Phonology\",\"FirstCategoryId\":\"98\",\"ListUrlMain\":\"https://doi.org/10.5334/LABPHON.108\",\"RegionNum\":2,\"RegionCategory\":\"文学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"0\",\"JCRName\":\"LANGUAGE & LINGUISTICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Laboratory Phonology","FirstCategoryId":"98","ListUrlMain":"https://doi.org/10.5334/LABPHON.108","RegionNum":2,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"LANGUAGE & LINGUISTICS","Score":null,"Total":0}
Individual differences and patterns of convergence in prosody perception
The challenge of prosodic annotation is reflected in commonly reported variability among trained annotators in the assignment of prosodic labels. The present study examines individual differences in the perception of prosody through the lens of prosodic annotation. First, Generalized Additive Mixed Models (GAMMs) reveal the non-linear pattern of some acoustic cues on the perception of prosodic features. Second, these same models reveal that while some of the untrained annotators are using these cues to determine prosodic features, the magnitude of effect differs quite dramatically across the annotators. Finally, the trained annotators follow the same cues as subsets of the untrained annotators, but present a much stronger effect for many of the cues. The findings show that while prosody perception is systemically related to acoustic and contextual cues, there are also individual differences that are limited to the selection and magnitude of the factors that influence prosodic rating, and the relative weighting among those factors.