Simulation of teacher-learner interaction in English language pronunciation learning

Second language (L2) learning is a complex process that is difficult to model. This work aims to develop a computational model of the teacher–learner interaction as used for L2 learning. The teacher model simulates a native English speaker, which uses repetition as a teaching strategy, while the learner model simulates a native Chinese speaker at an early stage of L2 English learning. Joint simulation may allow valuable insights into the entire learning process. In this study, speakers from the speechocean762 corpus were enlisted, using a word list that includes phonemes known to pose difficulties for Chinese speakers. The similarity between the output of the learning process and real learner data is evaluated using MCD, PPG, and wav2vec 2.0 distortion measures. The results indicate that the similarity between the process output and real learners with low proficiency is higher compared to that with real learners with high proficiency