This research aims to examine both the prosodic-acoustic features and the perceptual correlates of foreign-accented English and foreign-accented Brazilian Portuguese and check how the speakers' productions of foreign and native accents are correlated to the listeners' perception. In the Methodology, we conducted a speech production procedure with a group of American speakers of L2 Brazilian Portuguese and a group of Brazilian speakers of L2 English, and a speech perception procedure in which we performed voice lineups for both languages.For the speech production statistical analysis, we ran Generalized Additive Models to evaluate the effect of the language groups on each class (metric or prosodic-acoustic) of features controlled for the smoothing effect of the covariate(s) of the opposite class. For the speech perception statistical analysis, we ran a Kruskal-Wallis test and a post-hoc Dunn's test to evaluate the effect of the voices of the lineups on the scores judged by the listeners. We nevertheless conducted acoustic (voice) similarity tests based on Cosine and Euclidean distances. Results showed significant acoustic differences between the language groups in terms of variability of the f0, duration, and voice quality. For the lineups, the results indicated that prosodic features of f0, intensity, and voice quality correlated to the listeners' perceived judgments.
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J Vis Exp
September 2024
Institute of Language Studies, Department of Linguistics, University of Campinas (Universidade de Campinas).
This research aims to examine both the prosodic-acoustic features and the perceptual correlates of foreign-accented English and foreign-accented Brazilian Portuguese and check how the speakers' productions of foreign and native accents are correlated to the listeners' perception. In the Methodology, we conducted a speech production procedure with a group of American speakers of L2 Brazilian Portuguese and a group of Brazilian speakers of L2 English, and a speech perception procedure in which we performed voice lineups for both languages.For the speech production statistical analysis, we ran Generalized Additive Models to evaluate the effect of the language groups on each class (metric or prosodic-acoustic) of features controlled for the smoothing effect of the covariate(s) of the opposite class.
View Article and Find Full Text PDFMemory
January 2023
Department of Psychology, Nottingham Trent University, Nottingham, United Kingdom.
Voice identification parades can be unreliable, as earwitness responses are error-prone. In this paper we tested performance across serial and sequential procedures, and varied pre-parade instructions, with the aim of reducing errors. The participants heard a target voice and later attempted to identify it from a parade.
View Article and Find Full Text PDFCogn Sci
June 2021
Department of Psychology, University of Toronto.
The existence of the Language Familiarity Effect (LFE), where talkers of a familiar language are easier to identify than talkers of an unfamiliar language, is well-documented and uncontroversial. However, a closely related phenomenon known as the Other Accent Effect (OAE), where accented talkers are more difficult to recognize, is less well understood. There are several possible explanations for why the OAE exists, but to date, little data exist to adjudicate differences between them.
View Article and Find Full Text PDFJ Exp Child Psychol
February 2021
Department of Psychology, University of Toronto Mississauga, Mississauga, Ontario L5L 1C6, Canada.
Previous studies have shown that talker recognition by young children continues to improve into late childhood. But why might this be the case? Are children's gradually improving talker recognition abilities driven primarily by general maturational factors in the cognitive or perceptual domain (general maturation hypothesis), or are these improvements primarily linked to children's increasingly sophisticated linguistic knowledge (language attunement hypothesis)? In the current study, we addressed this question by testing monolingual English-speaking 5- and 6-year-olds (N = 80) on their ability to recognize talkers in a familiar language (i.e.
View Article and Find Full Text PDFSci Justice
November 2019
Forensic Speech Science Laboratory, Aston Institute for Forensic Linguistics, and Centre for Forensic Data Science, Department of Computer Science, Aston University, Birmingham, England, United Kingdom; Forensic Evaluation Ltd, Birmingham, England, United Kingdom. Electronic address:
The present paper proposes and demonstrates a method for assessing strength of evidence when an earwitness claims to recognize the voice of a speaker who is familiar to them. The method calculates a Bayes factor that answers the question: What is the probability that the earwitness would claim to recognize the offender as the suspect if the offender was the suspect versus what is the probability that the earwitness would claim to recognize the offender as the suspect if the offender was not the suspect but some other speaker from the relevant population? By "claim" we mean a claim made by a cooperative earwitness not a claim made by an earwitness who is intentionally deceptive. Relevant data are derived from naïve listeners' responses to recordings of familiar speakers presented in a speaker lineup.
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