wjq-learning / zuco-benchmark

ZuCo Reading Task Classification Benchmark using EEG and Eye-Tracking Data

Welcome to the ZuCo Benchmark on Reading Task Classification!

🧭 Starting from here you can:

📖 Read the manuscript.

ℹ️ Gather more information on zuco-benchmark.com

💻 Look at our code for creating the baseline results

🏆 Create your own models and participate in our challenge at EvalAI

About ZuCo and the Reading Task Classification

The Zurich Cognitive Language Processing Corpus (ZuCo 2.0) is a dataset combining EEG and eye-tracking recordings from subjects reading natural sentences as a resource for the investigation of the human reading process in adult English native speakers.

The benchmark consists of a cross-subject classification to distinguish between normal reading and task-specific information searching.

How Can I Use This Repository?

This repository is supposed to give you a starting point to participate in our challenge.
To run the code, follow the steps:

Dependecies

1. Install pip
2. Create a virtual environment and activate it
3. Run pip install -r requirements.txt

Data

⚠️ Warning: the complete dataset contains about 70GB of files
You can also download individual files from the OSF
To download the whole dataset, execute
bash get_data.sh

Computing the Baseline Results

cd src
Select feature-set and other configurations in config.py.
Run the code to produce baseline predictions with the SVM and your configurations:
python benchmark_baseline.py
Use the code as a starting point for trying different models or extracting your own features.