Pronunciation Quality Scoring Algorithm Based on Universal Background Model
Jing Li · Jisuanji gongcheng · 2008
This paper presents a new algorithm which can assess the pronunciation quality of the English spoken by Chinese students.The new algorithm uses Gaussian Mixture Model(GMM)and Universal Background Model(UBM),which is successfully used in speaker verification.It calculates the duration normalized log-likelihood ratio of each phone as phonemic pronunciation scores.It combines each phonemic score to obtain the overall pronunciation quality.The algorithm is evaluated by using a corpus of non-native speech.Experimental results show that the approach outperforms other assessment algorithms on correlations with expert scores at the sentence level.In the test database,this method obtains high correlation(0.700).