Tag Archives: Statistics

Two Heads Are Better Than One: Artificial Intelligence & The Use of CycleGAN in Generating Handwritten Chinese Characters

These days, even a two-year-old knows how to use a computer! We are all very familiar with how computers fetch and display data, but can they also make decisions about data? This idea is explored by artificial intelligence (AI), which refers to computer systems that perform tasks that normally require human intelligence. Some examples include speech recognition and decision-making. In simpler terms, it is the ability of a computer to learn from input data to generate new output data, hence why it is also known as machine learning. While we may not always be aware, we are subjected to AI every day! Prior to reading this, you may have been watching a Netflix-suggested movie or have come across a new artist on Spotify that just so happens to be exactly your style. There are countless ways that AI is being used throughout different industries, and continues to be researched in order to reach its full potential.

An Introduction To Artificial Intelligence (AI)
Video produced by SO Group 1

 

Recent application of AI in research

Researchers Bo Chang and Qiong Zhang, PhD students from the Statistics department at the University of British Columbia, have used a form of AI called CycleGAN, to investigate the generation of Chinese handwritten characters. Their research, which was published this year, is fundamental to the preservation of Chinese culture and handwriting styles of famous calligraphers in China’s history, such as Wang Xizhi. Unlike letters in the English alphabet, Chinese is made up of logographic characters. These characters represent a word or a phrase, and there are over 80,000 of them in the Chinese language! This large number of characters has limited research in the past, but this obstacle was tackled in this study using the CycleGAN method.

calligraphy by Wang Xizhi

Famous Chinese Calligraphy by Wang Xizhi
Image Source: flickr
Photographer: Margaret

 

Use of CycleGAN in Chinese handwritten characters generation

The goal of the procedure was having the machine learn the transformations that are required to go from an inputted pre-made font to an output of personalized handwritten font. In order to do this, evaluation metrics consisting of style discrepancy and content accuracy were established. The specific use of CycleGAN, contributes to achieving accurate output characters by using two machines instead of one. One guarantees that generated handwritten characters look like the real style that is desired, and the second, which is cyclic, guarantees that handwritten characters generated from pre-made font will reverse back to the original pre-made font.

Experimental results through this study demonstrated the efficacy of this method of Chinese character generation, showing it to be superior or on-par with other systems. For example, characters were less likely to have missing or additional strokes compared to other systems.

An interview with Bo Chang & Qiong Zhang on
“Generating Handwritten Chinese Characters using CycleGAN”
Audio produced by SO Group 1 with special thanks to Bo Chang & Qiong Zhang

 

Overall, this method proves to be preferred due to generation of more accurate and desirable results. While this research isn’t being further pursued, many around the world have already shown interest in using and modifying the code! This method may also prove to be useful in generation of characters in other languages.

Group 1: Shadi Elmi, Allison Chiang, Wenyu Zhao & Hao Huang

Could Every Introductory Statistics Student Become A Consultant?

Many Statistics students may wonder how the methods and tests learned in class can be applied outside of class. Especially, some test statistics and p-values that confuse students seem boring and meaningless, yet their applications are rarely mentioned in most of elementary statistics courses.

Example of Statistical Test

Credit: WikiPedia

An article published recently described an experiment to turn introductory statistics students into consultants. Adam F. Childers, James Madison University found that guiding students to analyze real data from Facebook helps them learn how to use statistical methods and provide useful suggestions for local businesses and organizations. The project promotes students’ interest in different statistics methods and enhances their understanding of statistics and its value further.

Motivate Students’ Interest

The author built up a semester-long project in his introductory statistics course, which provided an opportunity for students to learn descriptive and inferential statistics by applying it to real-world Facebook data. Students were split up into different groups to cooperate with local organizations. During the project, students had the chance to understand how their organization uses Facebook, which they could use for data analysis. Thanks to the project, students were put in an active position to help companies make better decisions. It was a good motivation for students to learn to apply statistics methods, which is exactly what the whole project was mainly dependent on.

Are statistics boring?

Credit: WordPress

Better to Understand Statistics

Also, students were asked to write a report about previous findings, which was a crucial part of the project according to Adam’s article. It was aimed to enable students to understand statistics. I agree with Adam for the same reason that students need to understand and apply others’ researches in case that they encounter any potential problem in the project.

Comprehend Statistics’ Real-Life Value

Finally, students needed to show their research results to their partner organizations. It was the most exciting part of the project. If I had the chance to participate in the project, I would have been proud of presenting my findings, obtained by statistics methods based on the data acquired from Facebook, to my partner organization. I could have known how useful my suggestions were to the organization—which is meaningful because all work done in the project would help the organization to grow better in the real world rather than merely concluding a rejection of null hypothesis on paper.

YouTube Preview Image

Credit:YouTuBe

No matter the suggestions worked or not, the participating students all took their first steps to become consultants. In my opinion, the most important thing for consulting is not just doing theoretical analysis on paper and make a decent conclusion but instead, applying your findings in the real world and validating the results. There are many unmeasurable variables varying from time to time in the real world that are missing on paper. Thus, there is no better way to learn better than doing a real-world application. Not only introductory students, graduate students also need to pay attention to this problem, because after all, statistics is a powerful tool to solve issues in real life.

Hao Huang