Predicting Speech Errors in Mandarin Based on Word Frequency

Abstract

This paper investigates the effect of word frequency on the occurrence of speech errors in Mandarin. A corpus of 390 speech errors along with their surrounding linguistic context was gathered. The information of word frequency was extracted from the Academia Sinica Corpus. Our analysis with a computational classifier based on conditional inference trees shows that intended words having a frequency lower than words of the surrounding context are more likely to generate speech errors.