Semantic predictability and adaptation to nonnative speech

Autor: Tessa Bent, Melissa M. Baese-Berk, Kayla Walker
Rok vydání: 2022
Předmět:
Zdroj: JASA express letters. 1(1)
ISSN: 2691-1191
Popis: Listeners improve their ability to understand nonnative speech through exposure. The present study examines the role of semantic predictability during adaptation. Listeners were trained on high-predictability, low-predictability, or semantically anomalous sentences. Results demonstrate that trained participants improve their perception of nonnative speech compared to untrained participants. Adaptation is most robust for the types of sentences participants heard during training; however, semantic predictability during exposure did not impact the amount of adaptation overall. Results show advantages in adaptation specific to the type of speech material, a finding similar to the specificity of adaptation previously demonstrated for individual talkers or accents.
Databáze: OpenAIRE