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Listeners dynamically adjust speech perception based on context, down-weighting less important acoustic cues like duration when processing accented speech. This statistical learning applies to both word parts and longer speech elements.

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Area of Science:

  • Psycholinguistics
  • Auditory Neuroscience
  • Speech Perception

Background:

  • Speech perception involves integrating multiple acoustic dimensions.
  • Perceptual weights of acoustic dimensions dynamically adjust to context.
  • It is debated whether suprasegmental speech features are perceived categorically.

Purpose of the Study:

  • Investigate dynamic perceptual weighting of acoustic dimensions in suprasegmental speech perception.
  • Determine if short-term statistical learning extends to categorical perception of word emphasis.
  • Examine the role of fundamental frequency (F0) and duration in processing accented speech.

Main Methods:

  • Participants categorized a two-word phrase with typical and atypical covariation of F0 and duration.
  • An artificial 'accent' manipulated the correlation between F0 and duration.
  • Listeners' categorization decisions were analyzed to infer perceptual weighting.

Main Results:

  • Listeners rapidly down-weighted the secondary acoustic dimension (duration) when processing accented speech.
  • This demonstrates rapid adaptation to short-term statistical regularities in speech.
  • Evidence suggests suprasegmental features are processed categorically.

Conclusions:

  • Dimension-based statistical learning is a widespread phenomenon in speech perception.
  • Listeners dynamically adjust acoustic evidence weighting for suprasegmental decisions.
  • Speech perception extends both segmental and suprasegmental categorization through statistical learning.