Improving Human Scoring of Prosody Using Parametric Speech Synthesis

In this study, HMM-based speech synthesis from an average model of native speakers was utilized. The experimental result shows that the proposed method can improve scoring reliability, which is confirmed by an increase in the inter-rater correlation. We also build an automatic pronunciation evaluation system trained from non-native speech databases with scores given by either the conventional and proposed methods, and compare the performance of the systems. The result shows that the predicted pronunciation scores matched the human-rated scores; the human-machine correlation produced a score of 0.87, while the conventional scoring method produced a score of 0.74.
Source: Speech Communication - Category: Speech-Language Pathology Source Type: research