Speech perception is not static. Within seconds of hearing a new voice, the brain begins to adapt. Recent analysis across multiple datasets (Valdes et al., 2025) shows that cortical tracking of the sound acoustics drops markedly within the first 20 seconds of exposure of a familiar voice. However, when listeners encounter a genuinely novel speaker, tracking does not decrease in the same way (Piazza et al., 2026), pointing to a habituation period during which the brain accumulates speaker‑specific information until it builds an appropriate acoustic‑to‑linguistic mapping. One possibility is that reduced tracking reflects greater efficiency: once the mapping is established, less neural machinery is needed to decode the signal.
Crucially, this sound acoustics tracking decrease also occurs for music (Valdes et al., 2025), so it is not unique to speech. What, then, might be special about language familiarity and acoustic‑to‑linguistic mapping? This project will aim to answer this question by leveraging multiple existing EEG datasets. By systematically reanalysing neural responses across novel versus familiar speakers, and by tracking features that are unique to speech (phonemic and semantic content), we can isolate what makes language adaptation different from domain‑general auditory habituation. Outcomes will have direct implications for the neurophysiology of speech processing, language development, and listening difficulties.
You will join an interdisciplinary research team composed of the principal investigator, three postdoctoral researchers, six PhD students, and two research assistants. The team meets weekly to discuss exciting ongoing work from within and outside the team, which is also an opportunity for Master’s students to experience research life and learn about the latest advances in brain and generative AI research (especially speech, language, and music processing).
Lab website: https://diliberg.net