SPIRE-SST: An automatic web-based self-learning tool for syllable stress tutoring (SST) to the second language learners

Abstract

Correct stress placement on the syllables in a word or word groups is important in the spoken communication. Thus, incorrect syllable stress, typically made by second language (L2) learners, could result in miscommunication. In this demo, we present SPIRE-SST tool that tutors to learn correct stress patterns in a self-learning manner. Thus, the proposed tool could also benefit the learners without any access to the effective training methods. For this, we design a front-end containing self-explanatory instructions that can be easily followed by the user. Using the front-end, learners can submit their audio to the back-end and can view the corresponding feedback from the back-end. In the back-end, we divide the entire audio from the learner into syllable segments and detect each syllable as stressed or unstressed. Using these stress markings, we compute a score representing the stress quality in comparison with the ground-truth stress markings and send it to the front-end as a feedback. We also send a set of three features by comparing the audio from the expert and learner as the feedback, which we assume to be useful for correcting the pronunciation errors. � 2018 International Speech Communication Association. All rights reserved.