  Computer-Assisted Pronunciation Training (CAPT) plays an important role in
language learning. Conventional ASR-based CAPT methods require expensive
annotation of the ground truth pronunciation for the supervised training.
Meanwhile, certain undefined non-native phonemes cannot be correctly classified
into standard phonemes, making the annotation process challenging and
subjective. On the other hand, ASR-based CAPT methods only give the learner
text-based feedback about the mispronunciation, but cannot teach the learner
how to pronounce the sentence correctly. To solve these limitations, we propose
to use the acoustic unit (AU) as the intermediary feature for both
mispronunciation detection and correction. The proposed method uses the masked
AU sequence and the target phonemes to detect the error AU and then corrects
it. This method can give the learner speech-based self-imitating feedback,
making our CAPT powerful for education.
