Background and Objectives

In this master’s thesis, we investigate how the brain processes spoken language in everyday life, focusing in particular on the level of individual phonemes, words, and sentence positions.
The work is based on an existing EEG dataset, in which participants listened to multiple speakers.

The aim is to replicate findings from an existing study, with a special focus on:

the processing of individual phonemes and words,

differences in processing between sentence beginnings and endings,

the neural representation of filler words such as “uhm,” “well,” and similar expressions.

For the analyses, we use Temporal Response Functions (TRFs) – a method that allows modeling time-resolved EEG responses to continuous speech.

Your Role as a Master’s Student

As part of this project, you will:

work intensively with an existing EEG dataset,

annotate speech stimuli (e.g., phoneme, word, and sentence boundaries, filler words),

conduct TRF analyses to identify language-specific neural responses,

interpret and critically discuss the results in comparison to a previous study.

What We Offer

Access to a unique dataset combining natural speech and EEG,

A clear research question closely linked to current work in speech processing research,

Methodological supervision from a team with expertise in language processing and EEG,

The opportunity to work at the intersection of neurolinguistics, signal processing, and methodological innovation.

What We Are Looking For

Strong MATLAB skills, especially in handling EEG data,

Interest in language-related cognition, neurolinguistics, or EEG methods,

Ability to approach complex data analyses in a structured and analytical manner.

If you are fascinated by the neural processing of language and enjoy methodological deep dives, we look forward to your application!

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