In this paper we describe an automatic pronunciation error detection and feedback generation system for non-native second language learners by using deep acoustic model based on factorized TDNN and language model with phoneme error model. Our system builds language model considering phoneme error patterns and gives a useful feedback for learners. Deep acoustic model consists of TDNN-F with grouped fully-connected layers and shuffle operation. This network architecture maintains recognition accuracy like traditiona…