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Contextual variability during speech-in-speech recognition.

Susanne Brouwer1, Ann R Bradlow1

  • 1Department of Linguistics, Northwestern University, 2016 Sheridan Road, Evanston, Illinois 60208 s.m.brouwer@uu.nl, abradlow@northwestern.edu.

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Summary
This summary is machine-generated.

Speech recognition performance in mixed-language backgrounds depends on language predictability. Varying background languages (English/Dutch) impacts how well listeners recognize English speech, especially with predictable context.

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Area of Science:

  • Auditory perception
  • Speech processing
  • Psychoacoustics

Background:

  • Understanding speech recognition in complex auditory environments is crucial.
  • Background noise, especially competing speech, significantly impacts intelligibility.
  • The effect of varying background languages on speech-in-speech recognition is not fully understood.

Purpose of the Study:

  • To investigate how background language variation influences English speech recognition.
  • To compare listener performance in pure versus mixed-language background conditions.
  • To determine if contextual predictability of background language affects speech perception.

Main Methods:

  • English listeners completed an English sentence recognition task.
  • Background conditions included pure babble (English or Dutch) and mixed babble (English/Dutch/quiet).
  • Performance on identical trials was compared across pure and mixed background conditions.

Main Results:

  • Speech-in-speech recognition performance is sensitive to contextual variation in background language.
  • The target-background language mismatch/match influences recognition accuracy.
  • Trial difficulty relative to surrounding trials modulates the effect of background language variation.

Conclusions:

  • Auditory contextual cues, including background language predictability, play a significant role in speech recognition.
  • Listeners' ability to adapt to changing background language environments affects intelligibility.
  • Findings have implications for understanding speech perception in real-world, noisy acoustic settings.