The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
The Effect of Social Information on the Perception of Sociolinguistic Variables
Abstract
Forty-one Detroit-area residents were given perceptual tests in which they were asked to choose from a set of resynthesized vowels the tokens that they felt best matched the vowels they heard in the speech of a fellow Detroiter. Half of the respondents were told that the speaker was from Detroit, whereas half were told that she was from Canada. Respondents given the Canadian label chose raised-diphthong tokens as those present in the dialect of the speaker, whereas those given the Michigan label did not. Respondents given the Michigan label chose vowels that were quite different from the Northern Cities Chain-Shifted variety present in the speaker’s dialect. Because the “speaker’s” perceived nationality was the only aspect that varied between the two groups of respondents, this label alone must have caused the difference in the selection of tokens. This indicates that listeners use social information in speech perception.
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Cites
Hearing lips and seeing voices
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Control Methods Used in a Study of the Vowels
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“Instead, the respondents given the Michigan label chose a token quite similar to canonical /ε / (see Peterson & Barney, 1952).”
BackgroundInfluentialInternational journal of the sociology of language 109
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2. Gradient and Visual Speaker Normalization in the Perception of Fricatives
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Metadata
- Authors
- Niedzielski, N.
- Venue
- Journal of Language and Social Psychology
- Publisher
- SAGE Publications
- Published
- 1999-03
- Volume
- 18
- Issue
- 1
- Pages
- 62-85
- ISSN
- 0261-927X (ISSN-L)
- 1552-6526
- OpenAlex
- W2164375248
- Cited by
- 655
- References
- 10
- FWCI
- 10.19
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
