Paper: Improved pronunciation features for construct-driven assessment of non-native spontaneous speech

ACL ID N09-1050
Title Improved pronunciation features for construct-driven assessment of non-native spontaneous speech
Venue Human Language Technologies
Session Main Conference
Year 2009
Authors

This paper describes research on automatic as- sessment of the pronunciation quality of spon- taneous non-native adult speech. Since the speaking content is not known prior to the assessment, a two-stage method is developed to first recognize the speaking content based on non-native speech acoustic properties and then forced-align the recognition results with a reference acoustic model reflecting native and near-native speech properties. Features related to Hidden Markov Model likelihoods and vowel durations are extracted. Words with low recognition confidence can be excluded in the extraction of likelihood-related fea- tures to minimize erroneous alignments due to speech recognition errors. Our experiments on the TOEFL R©Practice Online test, an En- glish language assessment, suggest tha...