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Tuning in to clarity: How the brain tracks and remembers clear speech
Poster Session C, Saturday, September 13, 11:00 am - 12:30 pm, Field House
This poster is part of the Sandbox Series.
Sarah J, Woods1, Jack W Silcox1, Brennan R. Payne1; 1University of Utah
Consistent with the effortfulness hypothesis (Pichora-Fuller et al., 2016; Rabbitt, 1968) clear speech is often easier for listeners to process than conversational speech, leading to improved recall and recognition memory. However, the underlying mechanisms responsible for this facilitative effect remain unclear. One possibility is that clear speech enhances encoding of deeper lexical and semantic information, while another suggests that acoustic features are primarily responsible. To investigate this, we are conducting a study using continuous electroencephalography (EEG) in 80 older adults as they listen to both clear and conversational sentences embedded in background noise. All sentences are highly constraining and mixed with +3 dB speech-shaped noise created from averaged clear and conversational speech samples, ensuring consistent acoustic masking across conditions. Importantly, our participants represent a range of hearing acuities, which allows us to examine how individual differences in peripheral hearing may interact with the neural encoding of speech. Preliminary behavioral results indicate better recognition memory, more accurate cued recall of sentence-final words, and improved performance on grammaticality judgments for clear speech. To further explore the neural basis of these effects, we plan to conduct neural speech tracking analyses on the EEG data. Neural speech tracking provides a window into how well the brain encodes the speech signal and has been linked to both intelligibility and attentional engagement. Given the variety of existing speech tracking techniques and the variability in reported outcomes, this project will compare multiple approaches — including encoding, decoding, and cross-correlation methods, to assess the robustness and reliability of neural encoding metrics. By doing so, we aim to identify which aspects of neural speech tracking are most sensitive to the processing benefits of clear speech, and how these may differ as a function of hearing acuity. These analyses will be conducted following recent best-practice recommendations for frequency and time-frequency domain studies of neural time series (Keil et al., 2022). We predict that neural speech tracking will be stronger for clear than for conversational speech, and that individuals with poorer hearing will show reduced tracking fidelity. Furthermore, we expect the degree of neural tracking enhancement for clear speech to predict the behavioral memory benefit, linking perceptual encoding with downstream cognitive performance.
Topic Areas: Speech Perception,