A Study on Correcting Korean Pronunciation Error of Foreign Learners by Using Supporting Vector Machine Algorithm

• Published in: The International journal of advanced culture technology Vol. 8; no. 3; pp. 316 - 324
• Main Authors: Jang, Kyungnam, You, Kwang-Bock, Park, Hyungwoo
• Format: Journal Article
• Language: Korean
• Published: 2020
• Subjects: Support Vector Machine; and Korean Pronunciation; Machine Learning; Korean Learning
• ISSN: 2288-7202; 2233-7318

It has experienced how difficult People with foreign language learning, it is to pronounce a new language different from the native language. The goal of various foreigners who want to learn Korean is to speak Korean as well as their native language to communicate smoothly. However, each native language's vocal habits also appear in Korean pronunciation, which prevents accurate information transmission. In this paper, the pronunciation of Chinese learners was compared with that of Korean. For comparison, the fundamental frequency and its variation of the speech signal were examined and the spectrogram was analyzed. The Formant frequencies known as the resonant frequency of the vocal tract were calculated. Based on these characteristics parameters, the classifier of the Supporting Vector Machine was found to classify the pronunciation of Koreans and the pronunciation of Chinese learners. In particular, the linguistic proposition was scientifically proved by examining the Korean pronunciation of /ㄹ/ that the Chinese people were not good at pronouncing.