Sentence recognition in noise: The interplay between talker intelligibility, familiarity, and linguistic complexity

Abstract

Foreign-accented speech recognition is typically tested with linguistically simple sentences, which offer a limited window into speech processing. In this study, participants transcribed simple (i.e. mono-clausal, canonical declarative syntax) and complex (i.e. multi-clausal, non-canonical syntax, and/or passive voice) sentences in noise at two signal-to-noise ratios. The sentences were spoken by three talkers: one native, one high and one low intelligibility L2 English speaker. Unsurprisingly, recognition accuracy dropped with decreasing intelligibility and signal-to-noise ratio. Interestingly, accuracy dropped with increasing linguistic complexity only for the native and high intelligibility talkers. For the low intelligibility talker, sentence complexity did not affect recognition accuracy. This pattern of findings was present in mixed and blocked experimental designs, indicating no effect of familiarity with the talker. We argue that listeners employ qualitatively different speech processing strategies for low versus high intelligibility talkers, and suggest that this difference may be driven by the talker’s realization of prosodic structure. While native and high intelligibility talkers effectively encode the contrast between complex and simple sentences, low intelligibility talkers may not convey sufficient prosodic information, resulting in the recognition of both sentence types as non-hierarchically organized word sequences. [Work supported by Knowles Hearing Center, NIH grants R01-DC012289 and R01-DC005794.]