This repository hosts the scripts and resources to run our Jupyter/Google Colab-based Mandarin A-maze and Multilingual A-maze scripts. For more details about the purpose and experimental testing of this project, see the lab webpage for our HSP 2023 poster.
Project Contributors: Yizhi Tang, Lucy Yu-Chuan Chiang, Wei-Jie Zhou, Sohee Chung, Lisa Levinson
Please cite as: Levinson, L., Tang, Y., Chiang, L. Y.-C., Zhou, W.-J., & Chung, S. (2023, March 11). Multilingual A-maze: Generating Maze Experiments in Mandarin and Beyond (poster). 36th Annual Conference on Human Sentence Processing (HSP 2023), University of Pittsburgh. https://github.com/UMWordLab/multilingual_amaze/
The notebooks can be run on Google Colab without any local installation of Python. To do so, click on the "open in Colab" button at the top of the notebook.
We are currently working on more detailed documentation which should be available by the end of March 2023, but brief instructions are also provided within the notebooks themselves. If you have any questions, you can use the Discussions tab, and bugs or feature requests can be added as Issues.
Boyce, V., Futrell, R., & Levy, R. P. (2020). Maze made easy: Better and easier measurement of incremental processing difficulty. Journal of Memory and Language, 111, 104082. https://doi.org/10.1016/j.jml.2019.104082
Forster, Kenneth I., Christine Guerrera, and Lisa Elliot. 2009. “The Maze Task: Measuring Forced Incremental Sentence Processing Time.” Behavior Research Methods 41 (1): 163–71. https://doi.org/10.3758/BRM.41.1.163.
Witzel, Naoko, Jeffrey Witzel, and Kenneth Forster. 2012. “Comparisons of Online Reading Paradigms: Eye Tracking, Moving-Window, and Maze.” Journal of Psycholinguistic Research 41 (2): 105–28. https://doi.org/10.1007/s10936-011-9179-x.