Determining sentence pronunciation difficulty for non-native speakers
Jeesoo Bang, Gary Geunbae Lee · 2013
This paper investigates the features that determine the sentence pronunciation difficulty for Korean speakers of English.We selected three types of features: length, word frequency, and phonemes that Korean speakers generally replace with other phonemes.We used support vector machines and a multiple linear regression model to determine the pronunciation difficulty of given sentences, and measured the results with a five-fold cross validation.We demonstrated that these features could determine sentence pronunciation difficulty with an accuracy and a correlation coefficient sufficient for computer-assisted pronunciation training (CAPT) systems.The combination of all three feature types had the highest accuracy and correlation coefficient in determining sentence pronunciation difficulty.For single features, the length-based feature type was the most accurate in determining sentence pronunciation difficulty.The phoneme-specific feature type also had high accuracy.Length, phoneme, and word features can be used to guide the automatic choice of sentences for CAPT systems that depend on users' proficiency levels.