Abstract
Speaking clearly improves intelligibility particularly in noisy environments—a benefit that may be partly attributed to enhanced ease of speech segmentation. However, speech segmentation is facilitated by coarticulation (Fernandes et al., 2007), which may be reduced in hyper-articulated clear speech (Scarborough and Zellou, 2013). This study investigated the effect of clear speech on speech segmentation in quiet and in noise for native and non-native listeners with an artificial language (AL) learning experiment. Six trisyllabic AL words (e.g., /kutupi/) were produced by a native English speaker both clearly and conversationally. Six speech streams were created, each containing 20 pitch-flattened tokens of each AL word concatenated in random order without intervening pauses. In the learning phase, participants heard either conversational or clear AL speech streams in quiet or masked with speech-shaped noise. Next, in a two-alternative forced-choice test, participants identified the AL words spoken in quiet and in the style they were exposed to. Preliminary results showed that clear speech improved segmentation relative to conversational speech for native English listeners in quiet only. The results suggest that the use of exaggerated information about segment identity aids speech segmentation in optimal listening conditions but is disrupted under perceptual load.
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