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WIREs Cogn Sci
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Representation of speech variability

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Speech signals provide both linguistic information (e.g., words and sentences) as well as information about the speaker who produced the message (i.e., social‐indexical information). Listeners store highly detailed representations of these speech signals, which are simultaneously indexed with linguistic and social category membership. A variety of methodologies—forced‐choice categorization, rating, and free classification—have shed light on listeners’ cognitive‐perceptual representations of the social‐indexical information present in the speech signal. Specifically, listeners can accurately identify some talker characteristics, including native language status, approximate age, sex, and gender. Additionally, listeners have sensitivity to other speaker characteristics—such as sexual orientation, regional dialect, native language for non‐native speakers, race, and ethnicity—but listeners tend to be less accurate or more variable at categorizing or rating speakers based on these constructs. However, studies have not necessarily incorporated more recent conceptions of these constructs (e.g., separating listeners’ perceptions of race vs ethnicity) or speakers who do not fit squarely into specific categories (e.g., for sex perception, intersex individuals; for gender perception, genderqueer speakers; for race perception, multiracial speakers). Additional research on how the intersections of social‐indexical categories influence speech perception is also needed. As the field moves forward, scholars from a variety of disciplines should be incorporated into investigations of how listeners’ extract and represent facets of personal identity from speech. Further, the impact of these representations on our interactions with one another in contexts outside of the laboratory should continue to be explored. WIREs Cogn Sci 2017, 8:e1434. doi: 10.1002/wcs.1434 This article is categorized under: Linguistics > Language Acquisition Linguistics > Language in Mind and Brain Psychology > Language

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