# Upscaled image files for LEXTALE_CH
- **Author:** Kevin Tang [Department of English Language and Linguistics, Institute of English and American Studies, Heinrich Heine University Düsseldorf, Düsseldorf, 40225, Germany, kevin.tang@hhu.de; University of Florida, tang.kevin@ufl.edu]
- **Date:** 20/02/2024
## Summary
This project provides a higher resolution version (168 by 168 pixels) of the images originally used in LEXTALE_CH (Chan and Chang, 2023a). LEXTALE_CH (Chan and Chang 2018) is a quick, character-based proficiency test for Mandarin Chinese.
## Statement of need
The images from Chan and Chang (2023a) were of a low resolution of 42 by 42 pixels. While these are sufficient for the printed version of LEXTALE_CH Chan and Chang (2023b) or the web-based implementation of LEXTALE_CH (https://gasparl.github.io/lextale/), such a resolution is too low for a trial-by-trial implementation, e.g., single trial lexical decision.
Personal communication with one of the authors (Chang, personal communication, 19 Feburary 2024) suggests that the original methods of how these images were generated have been lost, while the **design** of the nonce characters can be found in Peng et al (1998).
## Implementation
The low resolution images were sourced from Chan, I. L., & Chang, C. B. (2023, August 31). Image files for LEXTALE_CH. https://doi.org/10.17605/OSF.IO/K64QW.
The images were then upscaled using Upscaler (v1.2.2) (Rana et al. 2023) [@Upscaler_Github_v122]. This tool can upscale and enhance a given image. The tool uses the image restoration algorithm, Real-ESRGAN (Wang et al. 2021) [@wang2021realesrgan], especially the ncnn implementation of Real-ESRGAN (https://github.com/xinntao/Real-ESRGAN-ncnn-vulkan).
## References
Chan, I. L., & Chang, C. B. (2018). LEXTALE_CH: A quick, character-based proficiency test for Mandarin Chinese. In A. B. Bertolini & M. J. Kaplan (Eds.), Proceedings of the 42nd Annual Boston University Conference on Language Development, vol. 1 (pp. 114–130). Somerville, MA: Cascadilla Press.
Chan, I. L., & Chang, C. B. (2023, August 31). Image files for LEXTALE_CH. https://doi.org/10.17605/OSF.IO/K64QW.
Chan, I. L., & Chang, C. B. (2023, August 31). PDF and DOC versions of LEXTALE_CH. https://doi.org/10.17605/OSF.IO/R3VS9
Rana, H., Sezer, O., & volkov. (2023). Upscaler. Retrieved from https://github.com/TheEvilSkeleton/Upscaler [Commit: 479bcb3, Accessed 20-02-2024]
Peng, Dan-ling, Li, Yan-ping, & Yang, Hui. (1997). Orthographic processing in the identification of Chinese characters. In Hsuan-Chih Chen (Ed.), Cognitive processing of Chinese and related Asian languages, pp. 85–108. Hong Kong: The Chinese University Press.
Wang, X., Xie, L., Dong, C., & Shan, Y. (2021). Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data. International Conference on Computer Vision Workshops (ICCVW).
### Bibtex entries
``@Misc{Upscaler_Github_v122,
title = {{U}pscaler},
Author = {Rana, Hari and Sezer, Onuralp and {volkov}},
howpublished = {\url{https://github.com/TheEvilSkeleton/Upscaler}},
year = {2023},
note = {[Commit: 479bcb3, Accessed 20-02-2024]},
}
@InProceedings{wang2021realesrgan,
author = {Xintao Wang and Liangbin Xie and Chao Dong and Ying Shan},
title = {Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data},
booktitle = {International Conference on Computer Vision Workshops (ICCVW)},
date = {2021}
}
``
