Assessment of non-native speech using vowel space characteristics

In this paper, we propose the idea of using the characteristics of a speaker's vowel space for automated assessment of second language (L2) pronunciation. Specifically, we adopt features that were shown in previous studies to be good indicators of native speaker intelligibility and clarity and apply them to L2 speech from non-native speakers. The features focus on three peripheral vowels (IY, AA, and OW) and measure a speaker's coverage of the vowel space. A pilot study and a large-scale corpus study involving read speech produced by native and non-native speakers were conducted in which the vowel space features were rank correlated with pronunciation scores provided by human listeners for the non-native speech and an assumed higher score for the native speech. The results of the studies show that several of the features achieve moderately high correlations with the pronunciation scores, supporting their usefulness for automated assessment of non-native speech. The feature with the best performance in the large-scale study was the F2 − F1 distance for IY, which achieved a correlation of 0.78 with pronunciation proficiency scores.