Automatic evaluation of spoken english fluency

This paper presents a method to automatically quantify the spoken English fluency skills of speakers. The focus of this work is to automatically compute a numeric score of spoken fluency that is correlated with the numerical score the human assessors would assign. The proposed method combines several novel prosodic and lexical features to compute the fluency score. It is shown that the prosodic and the lexical features provide complementary information for fluency evaluation. Extensive evaluation on human-labeled utterances shows that the proposed technique exhibits similar trends in performance and confusions as shown by human assessors. The proposed technique leads to 84.2% classification accuracy when the two extreme classes of fluency are considered.

• Type: Conference
• Year: 2009
• Where: ICASSP
• Authors: Om Deshmukh, Kundan Kandhway, Ashish Verma, Kartik Audhkhasi
• Keywords: Human Assessors, ICASSP 2009, Lexical Features, Signal Processing, Spoken English fluency