Automatic sentence stress feedback for non-native English learners

Publication Type:

Journal Article

Source:

Computer Speech & Language, Volume 41, p.29 - 42 (2017)

URL:

http://www.sciencedirect.com/science/article/pii/S0885230816301759

DOI:

http://dx.doi.org/10.1016/j.csl.2016.04.003

Keywords:

CALL

Abstract:

This paper proposes a sentence stress feedback system in which sentence stress prediction, detection, and feedback provision models are combined. This system provides non-native learners with feedback on sentence stress errors so that they can improve their English rhythm and fluency in a self-study setting. The sentence stress feedback system was devised to predict and detect the sentence stress of any practice sentence. The accuracy of the prediction and detection models was 96.6% and 84.1%, respectively. The stress feedback provision model offers positive or negative stress feedback for each spoken word by comparing the probability of the predicted stress pattern with that of the detected stress pattern. In an experiment that evaluated the educational effect of the proposed system incorporated in our \{CALL\} system, significant improvements in accentedness and rhythm were seen with the students who trained with our system but not with those in the control group.