Improvements to vowel categorization in non-native regional accents resulting from multiple- versus single-talker training: A computational approach

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Author(s)
Wright, Sarah M.
Shaw, Jason A.
Best, Catherine T.
Docherty, Gerry
Evans, Bronwen G.
Foulkes, Paul
Hay, Jennifer
Mulak, Karen
Griffith University Author(s)
Year published
2014
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Show full item recordAbstract
A computational modeling study was conducted using
multinomial logistic regression to predict whether exposure to
an unfamiliar regional accent of English would influence
vowel categorization in (1) the exposure accent, (2) the native
accent, and (3) another unfamiliar accent. We manipulated the
number of talkers in the exposure data to determine whether
talker variability influenced the efficacy of the training.
Results showed a multiple-talker training benefit for the
categorization of some vowels. Training also transferred to an
untrained accent. Finally, the models predicted that exposure
to an unfamiliar accent has a ...
View more >A computational modeling study was conducted using multinomial logistic regression to predict whether exposure to an unfamiliar regional accent of English would influence vowel categorization in (1) the exposure accent, (2) the native accent, and (3) another unfamiliar accent. We manipulated the number of talkers in the exposure data to determine whether talker variability influenced the efficacy of the training. Results showed a multiple-talker training benefit for the categorization of some vowels. Training also transferred to an untrained accent. Finally, the models predicted that exposure to an unfamiliar accent has a negative impact on vowel categorization in the native accent.
View less >
View more >A computational modeling study was conducted using multinomial logistic regression to predict whether exposure to an unfamiliar regional accent of English would influence vowel categorization in (1) the exposure accent, (2) the native accent, and (3) another unfamiliar accent. We manipulated the number of talkers in the exposure data to determine whether talker variability influenced the efficacy of the training. Results showed a multiple-talker training benefit for the categorization of some vowels. Training also transferred to an untrained accent. Finally, the models predicted that exposure to an unfamiliar accent has a negative impact on vowel categorization in the native accent.
View less >
Conference Title
Proceedings of the 15th Australasian International Conference on Speech Science and Technology
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Copyright Statement
© 2014 ASSTA. The attached file is reproduced here in accordance with the copyright policy of the publisher. Please refer to the conference's website for access to the definitive, published version.
Subject
Laboratory Phonetics and Speech Science