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Effects of type, token, and talker variability in speech processing efficiency

Phonetic variability across talkers imposes additional processing costs during speech perception, evident in performance decrements for mixed- vs. single-talker speech. However, within-talker phonetic variation across different utterances is another, relatively unexplored source of variability in speech, and it is unknown how processing costs from within-talker variation compare to those from between-talker variation. Because cognitive consequences of talker variability are typically measured from two-alternative forced- choice tasks, whereas naturalistic speech processing occurs in a much larger decision space, it is also unclear how the effects of across-talker and within-talker variability scale and interact when there are more options to choose between during word identification. Here, we measured response times in a speeded word identification task that factorially manipulated three dimensions of speech variability: number of talkers (one vs. four), number of target word choices (two vs. six), and number of talker-specific exemplars per word (one vs. eight). Across all eight experimental levels, larger decision spaces led to significantly slower word identification. Word identification was also slower in conditions with mixed talkers and conditions with multiple exemplars. However, performance decrements between mixed- vs. single-talker speech were only present when variability in the other two dimensions was low, but decrements between multi- vs. single-token speech were present under all conditions. This pattern of interactions suggests complex processing relationships between type, token, and talker variability and provides preliminary evidence for how both within- and between-talker variability impose additional processing costs in speech perception.

Identiferoai:union.ndltd.org:bu.edu/oai:open.bu.edu:2144/38729
Date09 November 2019
CreatorsKapadia, Alexandra Mervan
ContributorsPerrachione, Tyler K.
Source SetsBoston University
Languageen_US
Detected LanguageEnglish
TypeThesis/Dissertation
RightsAttribution 4.0 International, http://creativecommons.org/licenses/by/4.0/

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