## 1 Introduction  
South Korea, officially known as the Republic of Korea (ROK), is a country that is surrounded by other countries that do not adopt the Latin alphabet. South Korea also has an alphabet called \"Hangeul\", which consists of 10 vowel letters and 14 consonant letters [1,2]. The fact that they use \"Hangeul\" instead of the Latin alphabet creates a particular problem for a foreigner who lives in South Korea because it means that they have to learn how to read this alphabet and learn new vocabulary, sentence structures, etc.  
There are 1.96 million foreigners that have stayed in South Korea as of 2021, which includes 1.57 million long-term residents and 386,000 short-term residents [3]. With the high number of foreigners staying inside the country, South Korea created a test to measure foreigners' proficiency in the Korean language called the Test of Proficiency in Korean (TOPIK) which was first administered in 1997. This test has many purposes, including getting a job or an academic scholarship in South Korea. TOPIK has six proficiency levels, with level 1 being a beginner level and level 6 being an advanced level. According to [4], the TOPIK test is divided into two categories: regular and speaking. The standard category measures reading, writing, and listening comprehension, while the speaking category solemmly measures speaking proficiency. However, the TOPIK speaking test in 2021 only has two sessions, and it is still stated as a pilot operation for 1200 participants per session in five countries (a pilot session in 2022 is not yet available, and a regular session will be implemented in the second half of 2022). In this situation, the problem is that the TOPIK speaking score will be manually measured by an expert panel, which will take a considerable amount of time to process, significantly when the number of participants is increasing as it will be available for more countries. Therefore, it requires an innovative way to solve the problem.  
This paper is driven by NSDevil, a South Korean company that collaborates with the South Korean government to manage the TOPIK test across South Korea. The NSDevil plans to speed up and digitalize the scoring process of TOPIK speaking by developing a system that can generate the score automatically using AI. The motivation for this paper is to help reduce the overall time of the scoring process in the TOPIK speaking test. Therefore, implementing Artificial Intelligence (AI), such as Machine Learning (ML) or Deep Learning (DL), to generate the TOPIK speaking score automatically can help the expert panel to score the test and reduce the whole scoring process time. This idea also became a necessity of this study. The system requires a Speech-To-Text (STT) technology to transcribe the test participants' voices into the text to be fed into an ML or DL model to be evaluated further and then generate the score. Furthermore, one of the system's key features is high mobility and being lightweight. Thus the system has to be light enough to be carried and implemented anywhere without a complex configuration.  
With the collaboration with NSDevil, the development of the ideal future system is divided into several phases. The first phase compares the performance of the open-source STT engine to find which STT is optimal for Korean. The second phase, also the main objective of this paper, is to develop the first version of the mobile application using STT engines and the Sentence Transformer framework. The application allows users to record themselves reading a Korean sentence and automatically checks the similarity as a score percentage. The mobile application will be the basis of the third phase, implementing an ML or DL technology to generate scores without needing a similarity check.