The automatic assessment of non-native prosody: combining classical prosodic analysis with acoustic modelling
Florian Hönig, Tobias Bocklet, Korbinian Riedhammer, Anton M. Batliner, Elmar Nöth · 2012
In earlier studies, we employed a large prosodic feature vector to assess the quality of L2 learner's utterances with respect to sentence melody and rhythm.In this paper, we combine these features with two standard approaches in paralinguistic analysis: (1) features derived from a Gaussian Mixture Model used as Universal Background Model (GMM-UBM), and (2) openSMILE, an open-source toolkit for extracting acoustic features.We evaluate our approach with English speech from 94 non-native speakers perceptually scored by 62 native labellers.GMM-UBM or openSMILE modelling alone yields lower performance than our prosodic feature vector; however, adding information from the GMM-UBM modelling or openSMILE by late fusion improves results.